View HyoSeonChoi's full-sized avatar
1 follower · 7 following

Achievements

Achievement: YOLOAchievement: Pull Sharkx2

Achievements

Achievement: YOLOAchievement: Pull Sharkx2

Organizations

@affctivai

Block or report HyoSeonChoi

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Content in all repositories owned by your account will be closed.
Maximum 250 characters. Please don’t include any personal information such as legal names or email addresses. Markdown is supported. This note will only be visible to you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse
HyoSeonChoi/README.md
🇰🇷 한국어

뇌파(EEG)와 감정 모델링을 중심으로 AI 연구를 수행했습니다.
Research to Product: 연구실 안에서 잘 되는 AI를 넘어, 실제 환경에서 쓰이는 AI로 나아가고자 합니다.
AI 데이터 신뢰성 · 도메인 기반 AI · 감성 컴퓨팅(Affective Computing)

학력

석사 논문

EEG 기반 감정 인식에서의 데이터 신뢰성 : 비신뢰 쌍 탐지 및 제거 프레임워크 개발
감성인공지능 연구실 | 지도교수님: 김병형

뇌파(EEG) 데이터와 감정 레이블 간 상관성이 저하된 데이터 샘플들을 딥러닝의 OOD(Out-of-Distribution) 탐지 기법으로 식별·제거하는 데이터 정제 프레임워크를 제안하였습니다. 세 개의 공개 데이터셋에서 기존 방법(RP) 대비 분류 정확도 최대 6.14%, AUROC 최대 4.33% 향상시켰습니다.

출판물

  • 2024.12International Conference[pdf][link][code]
    Detecting Concept Shifts under Different Levels of Self-awareness on Emotion Labeling
    27th International Conference on Pattern Recognition (ICPR 2024)
    Hyoseon Choi, Dahoon Choi, Netiwit Kaongeon, Byung Hyung Kim*

  • 2024.05Domestic Journal[pdf][link] 🏅KCC2023 우수논문상(인공지능분야) 초청논문 2023.06.19
    EEG 기반 감정 분류에서 MSP를 사용한 OOD 검출 적용
    정보과학회논문지 (Journal of KIISE)
    최효선, 최다훈, 김병형*

  • 2024.02International Conference[pdf][link][code]
    Multi-Output Regression for Integrated Prediction of Valence and Arousal in EEG-Based Emotion Recognition
    12th IEEE International Winter Conference on Brain-Computer Interface (WinterBCI)
    Hyoseon Choi, ChaeEun Woo, JiYun Kong, Byung Hyung Kim*

  • 2023.08International Journal[pdf][link]
    Decoding Auditory-Evoked Response in Affective States using Wearable Around-Ear EEG System
    Biomedical Physics and Engineering Express
    Jaehoon Choi, Netiwit Kaongoen, Hyoseon Choi, Minuk Kim, Byung Hyung Kim*, Sungho Jo*

기술 스택

언어PythonR | 딥러닝/MLPyTorchTensorFlowKerasscikit-learn | 데이터/시각화NumPyPandasSciPyMatplotlibSeaborn | 신호처리/통계MNEMATLABJamovi | 환경/도구JupyterGitLinux | CS정보처리기사2021.11.26 | 기타 경험HTMLCSSReactMongoDB
RAG Agent 구축LangChainLangGraphRAGChromaDB

기타경험

  • 영어 어학연수 호주, 브리즈번 2024.09.09—2025.09.19 | Greenwich English College 1년, Cambridge FCE B2 취득 2025.06.10
  • 국제 학회 포스터 발표 | ICPR 2024 인도, 콜카타 2024.12.01—2024.12.05
  • 공부한 책

연락처

Email

🇺🇸 English

Hi there 👋

Conducted AI research focused on EEG-based emotion modeling and data reliability.
Research to Product: Bridging the gap between lab-validated AI and AI that works in the real world.
AI Data Reliability · Domain-specific AI · Affective Computing

Education

Master's Thesis

Data Reliability in EEG-based Emotion Recognition: A Framework for Unreliable Data Pair Removal
Affective AI Lab | Advisor: Byung Hyung Kim

Proposed a data cleansing framework that identifies and removes unreliable EEG-label pairs — samples where the correlation between EEG signals and emotion labels is degraded — using deep learning-based Out-of-Distribution (OOD) detection. Achieved up to +6.14% improvement in classification accuracy and +4.33% in AUROC over the conventional method (Riemannian Potato) across three public datasets.

Publications

  • 2024.12International Conference[pdf][link][code]
    Detecting Concept Shifts under Different Levels of Self-awareness on Emotion Labeling
    27th International Conference on Pattern Recognition (ICPR 2024)
    Hyoseon Choi, Dahoon Choi, Netiwit Kaongeon, Byung Hyung Kim*

  • 2024.05Domestic Journal[pdf][link] 🏅Invited from KCC 2023 Best Paper 2023.06.19
    Applying OOD Detection using MSP in EEG-based Emotion Classification
    Journal of KIISE
    Hyoseon Choi, Dahoon Choi, Byung Hyung Kim*

  • 2024.02International Conference[pdf][link][code]
    Multi-Output Regression for Integrated Prediction of Valence and Arousal in EEG-Based Emotion Recognition
    12th IEEE International Winter Conference on Brain-Computer Interface (WinterBCI)
    Hyoseon Choi, ChaeEun Woo, JiYun Kong, Byung Hyung Kim*

  • 2023.08International Journal[pdf][link]
    Decoding Auditory-Evoked Response in Affective States using Wearable Around-Ear EEG System
    Biomedical Physics and Engineering Express
    Jaehoon Choi, Netiwit Kaongoen, Hyoseon Choi, Minuk Kim, Byung Hyung Kim*, Sungho Jo*

Tech Stack

LanguagesPythonR | Deep Learning/MLPyTorchTensorFlowKerasscikit-learn | Data/VisualizationNumPyPandasSciPyMatplotlibSeaborn | Signal Processing/StatisticsMNEMATLABJamovi | Environment/ToolsJupyterGitLinux | CSEngineer Information Processing2021.11.26 | Other ExperienceHTMLCSSReactMongoDB
RAG AgentLangChainLangGraphRAGChromaDB

Experience

  • English Language Program Brisbane, Australia 2024.09.09—2025.09.19 | Greenwich English College, Cambridge FCE B2 2025.06.10
  • International Conference Poster Presentation | ICPR 2024 Kolkata, India 2024.12.01—2024.12.05
  • Books I've Studied
    • Deep Learning from Scratch 1, 2 — Inha Univ. AI Club AiDL Study
    • Machine Learning + Deep Learning by Yourself, Do It! Deep Learning, AI and ML for Coders in Pytorch/Laurence Moroney

Contact

Email

Pinned Loading

  1. KoreanFashionKoreanFashionPublic

    Jupyter Notebook

  2. PyQt_TPMPyQt_TPMPublic

    Python

  3. affctivai/coglieraffctivai/coglierPublic

    Detecting Concept Shifts under Different Levels of Self-awareness on Emotion Labeling

    Python 1 2

  4. affctivai/MORaffctivai/MORPublic

    Multi-Output Regression for Integrated Prediction of Valence and Arousal in EEG-Based Emotion Recognition

    Jupyter Notebook 1 1

  5. algo-bojalgo-bojPublic

    Python

  6. fastapi-onnx-servingfastapi-onnx-servingPublic

    Image classification API using FastAPI + ONNX Runtime (ResNet-18)

    HTML

, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all 
 blocks\n(function() {\n function addCopyButtons() {\n document.querySelectorAll('pre code').forEach(function(codeBlock) {\n if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;\n codeBlock.parentElement.setAttribute('data-copy-added', 'true');\n \n var btn = document.createElement('button');\n btn.textContent = 'Copy';\n btn.style.cssText = 'position:absolute;top:4px;right:4px;padding:2px 8px;font-size:11px;background:#4ecdc4;border:none;border-radius:4px;color:#1a1a2e;cursor:pointer;opacity:0.7;transition:opacity 0.2s;';\n btn.onmouseover = function() { this.style.opacity = '1'; };\n btn.onmouseout = function() { this.style.opacity = '0.7'; };\n btn.onclick = function() {\n navigator.clipboard.writeText(codeBlock.textContent).then(function() {\n btn.textContent = 'Copied!';\n setTimeout(function() { btn.textContent = 'Copy'; }, 1500);\n });\n };\n codeBlock.parentElement.style.position = 'relative';\n codeBlock.parentElement.appendChild(btn);\n });\n }\n \n addCopyButtons();\n \n // Re-run on dynamic content\n var observer = new MutationObserver(addCopyButtons);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Add Copy Buttons to Code Blocks");
}
} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '

Skip to content
View HyoSeonChoi's full-sized avatar
1
follower
 · 7
following

Achievements
Achievement: YOLOAchievement: Pull Sharkx2
Achievements
Achievement: YOLOAchievement: Pull Sharkx2
Organizations
@affctivai

Block or report HyoSeonChoi

Block user

Prevent this user from interacting with your repositories and sending you notifications.
Learn more about blocking users.


You must be logged in to block users.


Content in all repositories owned by your account will be closed.


Maximum 250 characters. Please don’t include any personal information such as legal names or email addresses. Markdown is supported. This note will only be visible to you.

Report abuse

Contact GitHub support about this user’s behavior.
Learn more about reporting abuse.

Report abuse
HyoSeonChoi/README.md
🇰🇷 한국어
뇌파(EEG)와 감정 모델링을 중심으로 AI 연구를 수행했습니다.
Research to Product: 연구실 안에서 잘 되는 AI를 넘어, 실제 환경에서 쓰이는 AI로 나아가고자 합니다.
AI 데이터 신뢰성 · 도메인 기반 AI · 감성 컴퓨팅(Affective Computing)
학력
석사 논문
EEG 기반 감정 인식에서의 데이터 신뢰성 : 비신뢰 쌍 탐지 및 제거 프레임워크 개발
감성인공지능 연구실 | 지도교수님: 김병형
뇌파(EEG) 데이터와 감정 레이블 간 상관성이 저하된 데이터 샘플들을 딥러닝의 OOD(Out-of-Distribution) 탐지 기법으로 식별·제거하는 데이터 정제 프레임워크를 제안하였습니다. 세 개의 공개 데이터셋에서 기존 방법(RP) 대비 분류 정확도 최대 6.14%, AUROC 최대 4.33% 향상시켰습니다.
출판물
  • 2024.12International Conference[pdf][link][code]
    Detecting Concept Shifts under Different Levels of Self-awareness on Emotion Labeling
    
27th International Conference on Pattern Recognition (ICPR 2024)
    Hyoseon Choi, Dahoon Choi, Netiwit Kaongeon, Byung Hyung Kim*
  • 2024.05Domestic Journal[pdf][link] 🏅KCC2023 우수논문상(인공지능분야) 초청논문 2023.06.19
    EEG 기반 감정 분류에서 MSP를 사용한 OOD 검출 적용
    
정보과학회논문지 (Journal of KIISE)
    최효선, 최다훈, 김병형*
  • 2024.02International Conference[pdf][link][code]
    Multi-Output Regression for Integrated Prediction of Valence and Arousal in EEG-Based Emotion Recognition
    
12th IEEE International Winter Conference on Brain-Computer Interface (WinterBCI)
    Hyoseon Choi, ChaeEun Woo, JiYun Kong, Byung Hyung Kim*
  • 2023.08International Journal[pdf][link]
    Decoding Auditory-Evoked Response in Affective States using Wearable Around-Ear EEG System
    
Biomedical Physics and Engineering Express
    
Jaehoon Choi, Netiwit Kaongoen, Hyoseon Choi, Minuk Kim, Byung Hyung Kim*, Sungho Jo*
기술 스택
언어PythonR | 딥러닝/MLPyTorchTensorFlowKerasscikit-learn | 데이터/시각화NumPyPandasSciPyMatplotlibSeaborn | 신호처리/통계MNEMATLABJamovi | 환경/도구JupyterGitLinux | CS정보처리기사2021.11.26 | 기타 경험HTMLCSSReactMongoDB
RAG Agent 구축LangChainLangGraphRAGChromaDB
기타경험
  • 영어 어학연수 호주, 브리즈번 2024.09.09—2025.09.19 | Greenwich English College 1년, Cambridge FCE B2 취득 2025.06.10
  • 국제 학회 포스터 발표 | ICPR 2024 인도, 콜카타 2024.12.01—2024.12.05
  • 공부한 책
연락처
Email
🇺🇸 English
Hi there 👋
Conducted AI research focused on EEG-based emotion modeling and data reliability.
Research to Product: Bridging the gap between lab-validated AI and AI that works in the real world.
AI Data Reliability · Domain-specific AI · Affective Computing
Education
Master's Thesis
Data Reliability in EEG-based Emotion Recognition: A Framework for Unreliable Data Pair Removal
Affective AI Lab | Advisor: Byung Hyung Kim
Proposed a data cleansing framework that identifies and removes unreliable EEG-label pairs — samples where the correlation between EEG signals and emotion labels is degraded — using deep learning-based Out-of-Distribution (OOD) detection. Achieved up to +6.14% improvement in classification accuracy and +4.33% in AUROC over the conventional method (Riemannian Potato) across three public datasets.
Publications
  • 2024.12International Conference[pdf][link][code]
    Detecting Concept Shifts under Different Levels of Self-awareness on Emotion Labeling
    
27th International Conference on Pattern Recognition (ICPR 2024)
    Hyoseon Choi, Dahoon Choi, Netiwit Kaongeon, Byung Hyung Kim*
  • 2024.05Domestic Journal[pdf][link] 🏅Invited from KCC 2023 Best Paper 2023.06.19
    Applying OOD Detection using MSP in EEG-based Emotion Classification
    
Journal of KIISE
    Hyoseon Choi, Dahoon Choi, Byung Hyung Kim*
  • 2024.02International Conference[pdf][link][code]
    Multi-Output Regression for Integrated Prediction of Valence and Arousal in EEG-Based Emotion Recognition
    
12th IEEE International Winter Conference on Brain-Computer Interface (WinterBCI)
    Hyoseon Choi, ChaeEun Woo, JiYun Kong, Byung Hyung Kim*
  • 2023.08International Journal[pdf][link]
    Decoding Auditory-Evoked Response in Affective States using Wearable Around-Ear EEG System
    
Biomedical Physics and Engineering Express
    
Jaehoon Choi, Netiwit Kaongoen, Hyoseon Choi, Minuk Kim, Byung Hyung Kim*, Sungho Jo*
Tech Stack
LanguagesPythonR | Deep Learning/MLPyTorchTensorFlowKerasscikit-learn | Data/VisualizationNumPyPandasSciPyMatplotlibSeaborn | Signal Processing/StatisticsMNEMATLABJamovi | Environment/ToolsJupyterGitLinux | CSEngineer Information Processing2021.11.26 | Other ExperienceHTMLCSSReactMongoDB
RAG AgentLangChainLangGraphRAGChromaDB
Experience
  • English Language Program Brisbane, Australia 2024.09.09—2025.09.19 | Greenwich English College, Cambridge FCE B2 2025.06.10
  • International Conference Poster Presentation | ICPR 2024 Kolkata, India 2024.12.01—2024.12.05
  • Books I've Studied
    • Deep Learning from Scratch 1, 2 — Inha Univ. AI Club AiDL Study
    • Machine Learning + Deep Learning by Yourself, Do It! Deep Learning, AI and ML for Coders in Pytorch/Laurence Moroney
Contact
Email

Pinned
Loading
  1. KoreanFashionKoreanFashionPublic
    Jupyter Notebook
  2. PyQt_TPMPyQt_TPMPublic
    Python
  3. affctivai/coglieraffctivai/coglierPublic
    
Detecting Concept Shifts under Different Levels of Self-awareness on Emotion Labeling

    Python
1

2

  4. affctivai/MORaffctivai/MORPublic
    
Multi-Output Regression for Integrated Prediction of Valence and Arousal in EEG-Based Emotion Recognition

    Jupyter Notebook
1

1

  5. algo-bojalgo-bojPublic
    Python
  6. fastapi-onnx-servingfastapi-onnx-servingPublic
    
Image classification API using FastAPI + ONNX Runtime (ResNet-18)

    HTML

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix");
}
} catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
View HyoSeonChoi's full-sized avatar
1
follower
 · 7
following

Achievements
Achievement: YOLOAchievement: Pull Sharkx2
Achievements
Achievement: YOLOAchievement: Pull Sharkx2
Organizations
@affctivai

Block or report HyoSeonChoi

Block user

Prevent this user from interacting with your repositories and sending you notifications.
Learn more about blocking users.


You must be logged in to block users.


Content in all repositories owned by your account will be closed.


Maximum 250 characters. Please don’t include any personal information such as legal names or email addresses. Markdown is supported. This note will only be visible to you.

Report abuse

Contact GitHub support about this user’s behavior.
Learn more about reporting abuse.

Report abuse
HyoSeonChoi/README.md
🇰🇷 한국어
뇌파(EEG)와 감정 모델링을 중심으로 AI 연구를 수행했습니다.
Research to Product: 연구실 안에서 잘 되는 AI를 넘어, 실제 환경에서 쓰이는 AI로 나아가고자 합니다.
AI 데이터 신뢰성 · 도메인 기반 AI · 감성 컴퓨팅(Affective Computing)
학력
석사 논문
EEG 기반 감정 인식에서의 데이터 신뢰성 : 비신뢰 쌍 탐지 및 제거 프레임워크 개발
감성인공지능 연구실 | 지도교수님: 김병형
뇌파(EEG) 데이터와 감정 레이블 간 상관성이 저하된 데이터 샘플들을 딥러닝의 OOD(Out-of-Distribution) 탐지 기법으로 식별·제거하는 데이터 정제 프레임워크를 제안하였습니다. 세 개의 공개 데이터셋에서 기존 방법(RP) 대비 분류 정확도 최대 6.14%, AUROC 최대 4.33% 향상시켰습니다.
출판물
  • 2024.12International Conference[pdf][link][code]
    Detecting Concept Shifts under Different Levels of Self-awareness on Emotion Labeling
    
27th International Conference on Pattern Recognition (ICPR 2024)
    Hyoseon Choi, Dahoon Choi, Netiwit Kaongeon, Byung Hyung Kim*
  • 2024.05Domestic Journal[pdf][link] 🏅KCC2023 우수논문상(인공지능분야) 초청논문 2023.06.19
    EEG 기반 감정 분류에서 MSP를 사용한 OOD 검출 적용
    
정보과학회논문지 (Journal of KIISE)
    최효선, 최다훈, 김병형*
  • 2024.02International Conference[pdf][link][code]
    Multi-Output Regression for Integrated Prediction of Valence and Arousal in EEG-Based Emotion Recognition
    
12th IEEE International Winter Conference on Brain-Computer Interface (WinterBCI)
    Hyoseon Choi, ChaeEun Woo, JiYun Kong, Byung Hyung Kim*
  • 2023.08International Journal[pdf][link]
    Decoding Auditory-Evoked Response in Affective States using Wearable Around-Ear EEG System
    
Biomedical Physics and Engineering Express
    
Jaehoon Choi, Netiwit Kaongoen, Hyoseon Choi, Minuk Kim, Byung Hyung Kim*, Sungho Jo*
기술 스택
언어PythonR | 딥러닝/MLPyTorchTensorFlowKerasscikit-learn | 데이터/시각화NumPyPandasSciPyMatplotlibSeaborn | 신호처리/통계MNEMATLABJamovi | 환경/도구JupyterGitLinux | CS정보처리기사2021.11.26 | 기타 경험HTMLCSSReactMongoDB
RAG Agent 구축LangChainLangGraphRAGChromaDB
기타경험
  • 영어 어학연수 호주, 브리즈번 2024.09.09—2025.09.19 | Greenwich English College 1년, Cambridge FCE B2 취득 2025.06.10
  • 국제 학회 포스터 발표 | ICPR 2024 인도, 콜카타 2024.12.01—2024.12.05
  • 공부한 책
연락처
Email
🇺🇸 English
Hi there 👋
Conducted AI research focused on EEG-based emotion modeling and data reliability.
Research to Product: Bridging the gap between lab-validated AI and AI that works in the real world.
AI Data Reliability · Domain-specific AI · Affective Computing
Education
Master's Thesis
Data Reliability in EEG-based Emotion Recognition: A Framework for Unreliable Data Pair Removal
Affective AI Lab | Advisor: Byung Hyung Kim
Proposed a data cleansing framework that identifies and removes unreliable EEG-label pairs — samples where the correlation between EEG signals and emotion labels is degraded — using deep learning-based Out-of-Distribution (OOD) detection. Achieved up to +6.14% improvement in classification accuracy and +4.33% in AUROC over the conventional method (Riemannian Potato) across three public datasets.
Publications
  • 2024.12International Conference[pdf][link][code]
    Detecting Concept Shifts under Different Levels of Self-awareness on Emotion Labeling
    
27th International Conference on Pattern Recognition (ICPR 2024)
    Hyoseon Choi, Dahoon Choi, Netiwit Kaongeon, Byung Hyung Kim*
  • 2024.05Domestic Journal[pdf][link] 🏅Invited from KCC 2023 Best Paper 2023.06.19
    Applying OOD Detection using MSP in EEG-based Emotion Classification
    
Journal of KIISE
    Hyoseon Choi, Dahoon Choi, Byung Hyung Kim*
  • 2024.02International Conference[pdf][link][code]
    Multi-Output Regression for Integrated Prediction of Valence and Arousal in EEG-Based Emotion Recognition
    
12th IEEE International Winter Conference on Brain-Computer Interface (WinterBCI)
    Hyoseon Choi, ChaeEun Woo, JiYun Kong, Byung Hyung Kim*
  • 2023.08International Journal[pdf][link]
    Decoding Auditory-Evoked Response in Affective States using Wearable Around-Ear EEG System
    
Biomedical Physics and Engineering Express
    
Jaehoon Choi, Netiwit Kaongoen, Hyoseon Choi, Minuk Kim, Byung Hyung Kim*, Sungho Jo*
Tech Stack
LanguagesPythonR | Deep Learning/MLPyTorchTensorFlowKerasscikit-learn | Data/VisualizationNumPyPandasSciPyMatplotlibSeaborn | Signal Processing/StatisticsMNEMATLABJamovi | Environment/ToolsJupyterGitLinux | CSEngineer Information Processing2021.11.26 | Other ExperienceHTMLCSSReactMongoDB
RAG AgentLangChainLangGraphRAGChromaDB
Experience
  • English Language Program Brisbane, Australia 2024.09.09—2025.09.19 | Greenwich English College, Cambridge FCE B2 2025.06.10
  • International Conference Poster Presentation | ICPR 2024 Kolkata, India 2024.12.01—2024.12.05
  • Books I've Studied
    • Deep Learning from Scratch 1, 2 — Inha Univ. AI Club AiDL Study
    • Machine Learning + Deep Learning by Yourself, Do It! Deep Learning, AI and ML for Coders in Pytorch/Laurence Moroney
Contact
Email

Pinned
Loading
  1. KoreanFashionKoreanFashionPublic
    Jupyter Notebook
  2. PyQt_TPMPyQt_TPMPublic
    Python
  3. affctivai/coglieraffctivai/coglierPublic
    
Detecting Concept Shifts under Different Levels of Self-awareness on Emotion Labeling

    Python
1

2

  4. affctivai/MORaffctivai/MORPublic
    
Multi-Output Regression for Integrated Prediction of Valence and Arousal in EEG-Based Emotion Recognition

    Jupyter Notebook
1

1

  5. algo-bojalgo-bojPublic
    Python
  6. fastapi-onnx-servingfastapi-onnx-servingPublic
    
Image classification API using FastAPI + ONNX Runtime (ResNet-18)

    HTML

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length > 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms");
}
} catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
View HyoSeonChoi's full-sized avatar
1
follower
 · 7
following

Achievements
Achievement: YOLOAchievement: Pull Sharkx2
Achievements
Achievement: YOLOAchievement: Pull Sharkx2
Organizations
@affctivai

Block or report HyoSeonChoi

Block user

Prevent this user from interacting with your repositories and sending you notifications.
Learn more about blocking users.


You must be logged in to block users.


Content in all repositories owned by your account will be closed.


Maximum 250 characters. Please don’t include any personal information such as legal names or email addresses. Markdown is supported. This note will only be visible to you.

Report abuse

Contact GitHub support about this user’s behavior.
Learn more about reporting abuse.

Report abuse
HyoSeonChoi/README.md
🇰🇷 한국어
뇌파(EEG)와 감정 모델링을 중심으로 AI 연구를 수행했습니다.
Research to Product: 연구실 안에서 잘 되는 AI를 넘어, 실제 환경에서 쓰이는 AI로 나아가고자 합니다.
AI 데이터 신뢰성 · 도메인 기반 AI · 감성 컴퓨팅(Affective Computing)
학력
석사 논문
EEG 기반 감정 인식에서의 데이터 신뢰성 : 비신뢰 쌍 탐지 및 제거 프레임워크 개발
감성인공지능 연구실 | 지도교수님: 김병형
뇌파(EEG) 데이터와 감정 레이블 간 상관성이 저하된 데이터 샘플들을 딥러닝의 OOD(Out-of-Distribution) 탐지 기법으로 식별·제거하는 데이터 정제 프레임워크를 제안하였습니다. 세 개의 공개 데이터셋에서 기존 방법(RP) 대비 분류 정확도 최대 6.14%, AUROC 최대 4.33% 향상시켰습니다.
출판물
  • 2024.12International Conference[pdf][link][code]
    Detecting Concept Shifts under Different Levels of Self-awareness on Emotion Labeling
    
27th International Conference on Pattern Recognition (ICPR 2024)
    Hyoseon Choi, Dahoon Choi, Netiwit Kaongeon, Byung Hyung Kim*
  • 2024.05Domestic Journal[pdf][link] 🏅KCC2023 우수논문상(인공지능분야) 초청논문 2023.06.19
    EEG 기반 감정 분류에서 MSP를 사용한 OOD 검출 적용
    
정보과학회논문지 (Journal of KIISE)
    최효선, 최다훈, 김병형*
  • 2024.02International Conference[pdf][link][code]
    Multi-Output Regression for Integrated Prediction of Valence and Arousal in EEG-Based Emotion Recognition
    
12th IEEE International Winter Conference on Brain-Computer Interface (WinterBCI)
    Hyoseon Choi, ChaeEun Woo, JiYun Kong, Byung Hyung Kim*
  • 2023.08International Journal[pdf][link]
    Decoding Auditory-Evoked Response in Affective States using Wearable Around-Ear EEG System
    
Biomedical Physics and Engineering Express
    
Jaehoon Choi, Netiwit Kaongoen, Hyoseon Choi, Minuk Kim, Byung Hyung Kim*, Sungho Jo*
기술 스택
언어PythonR | 딥러닝/MLPyTorchTensorFlowKerasscikit-learn | 데이터/시각화NumPyPandasSciPyMatplotlibSeaborn | 신호처리/통계MNEMATLABJamovi | 환경/도구JupyterGitLinux | CS정보처리기사2021.11.26 | 기타 경험HTMLCSSReactMongoDB
RAG Agent 구축LangChainLangGraphRAGChromaDB
기타경험
  • 영어 어학연수 호주, 브리즈번 2024.09.09—2025.09.19 | Greenwich English College 1년, Cambridge FCE B2 취득 2025.06.10
  • 국제 학회 포스터 발표 | ICPR 2024 인도, 콜카타 2024.12.01—2024.12.05
  • 공부한 책
연락처
Email
🇺🇸 English
Hi there 👋
Conducted AI research focused on EEG-based emotion modeling and data reliability.
Research to Product: Bridging the gap between lab-validated AI and AI that works in the real world.
AI Data Reliability · Domain-specific AI · Affective Computing
Education
Master's Thesis
Data Reliability in EEG-based Emotion Recognition: A Framework for Unreliable Data Pair Removal
Affective AI Lab | Advisor: Byung Hyung Kim
Proposed a data cleansing framework that identifies and removes unreliable EEG-label pairs — samples where the correlation between EEG signals and emotion labels is degraded — using deep learning-based Out-of-Distribution (OOD) detection. Achieved up to +6.14% improvement in classification accuracy and +4.33% in AUROC over the conventional method (Riemannian Potato) across three public datasets.
Publications
  • 2024.12International Conference[pdf][link][code]
    Detecting Concept Shifts under Different Levels of Self-awareness on Emotion Labeling
    
27th International Conference on Pattern Recognition (ICPR 2024)
    Hyoseon Choi, Dahoon Choi, Netiwit Kaongeon, Byung Hyung Kim*
  • 2024.05Domestic Journal[pdf][link] 🏅Invited from KCC 2023 Best Paper 2023.06.19
    Applying OOD Detection using MSP in EEG-based Emotion Classification
    
Journal of KIISE
    Hyoseon Choi, Dahoon Choi, Byung Hyung Kim*
  • 2024.02International Conference[pdf][link][code]
    Multi-Output Regression for Integrated Prediction of Valence and Arousal in EEG-Based Emotion Recognition
    
12th IEEE International Winter Conference on Brain-Computer Interface (WinterBCI)
    Hyoseon Choi, ChaeEun Woo, JiYun Kong, Byung Hyung Kim*
  • 2023.08International Journal[pdf][link]
    Decoding Auditory-Evoked Response in Affective States using Wearable Around-Ear EEG System
    
Biomedical Physics and Engineering Express
    
Jaehoon Choi, Netiwit Kaongoen, Hyoseon Choi, Minuk Kim, Byung Hyung Kim*, Sungho Jo*
Tech Stack
LanguagesPythonR | Deep Learning/MLPyTorchTensorFlowKerasscikit-learn | Data/VisualizationNumPyPandasSciPyMatplotlibSeaborn | Signal Processing/StatisticsMNEMATLABJamovi | Environment/ToolsJupyterGitLinux | CSEngineer Information Processing2021.11.26 | Other ExperienceHTMLCSSReactMongoDB
RAG AgentLangChainLangGraphRAGChromaDB
Experience
  • English Language Program Brisbane, Australia 2024.09.09—2025.09.19 | Greenwich English College, Cambridge FCE B2 2025.06.10
  • International Conference Poster Presentation | ICPR 2024 Kolkata, India 2024.12.01—2024.12.05
  • Books I've Studied
    • Deep Learning from Scratch 1, 2 — Inha Univ. AI Club AiDL Study
    • Machine Learning + Deep Learning by Yourself, Do It! Deep Learning, AI and ML for Coders in Pytorch/Laurence Moroney
Contact
Email

Pinned
Loading
  1. KoreanFashionKoreanFashionPublic
    Jupyter Notebook
  2. PyQt_TPMPyQt_TPMPublic
    Python
  3. affctivai/coglieraffctivai/coglierPublic
    
Detecting Concept Shifts under Different Levels of Self-awareness on Emotion Labeling

    Python
1

2

  4. affctivai/MORaffctivai/MORPublic
    
Multi-Output Regression for Integrated Prediction of Valence and Arousal in EEG-Based Emotion Recognition

    Jupyter Notebook
1

1

  5. algo-bojalgo-bojPublic
    Python
  6. fastapi-onnx-servingfastapi-onnx-servingPublic
    
Image classification API using FastAPI + ONNX Runtime (ResNet-18)

    HTML

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links");
}
} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '

Skip to content
View HyoSeonChoi's full-sized avatar
1
follower
 · 7
following

Achievements
Achievement: YOLOAchievement: Pull Sharkx2
Achievements
Achievement: YOLOAchievement: Pull Sharkx2
Organizations
@affctivai

Block or report HyoSeonChoi

Block user

Prevent this user from interacting with your repositories and sending you notifications.
Learn more about blocking users.


You must be logged in to block users.


Content in all repositories owned by your account will be closed.


Maximum 250 characters. Please don’t include any personal information such as legal names or email addresses. Markdown is supported. This note will only be visible to you.

Report abuse

Contact GitHub support about this user’s behavior.
Learn more about reporting abuse.

Report abuse
HyoSeonChoi/README.md
🇰🇷 한국어
뇌파(EEG)와 감정 모델링을 중심으로 AI 연구를 수행했습니다.
Research to Product: 연구실 안에서 잘 되는 AI를 넘어, 실제 환경에서 쓰이는 AI로 나아가고자 합니다.
AI 데이터 신뢰성 · 도메인 기반 AI · 감성 컴퓨팅(Affective Computing)
학력
석사 논문
EEG 기반 감정 인식에서의 데이터 신뢰성 : 비신뢰 쌍 탐지 및 제거 프레임워크 개발
감성인공지능 연구실 | 지도교수님: 김병형
뇌파(EEG) 데이터와 감정 레이블 간 상관성이 저하된 데이터 샘플들을 딥러닝의 OOD(Out-of-Distribution) 탐지 기법으로 식별·제거하는 데이터 정제 프레임워크를 제안하였습니다. 세 개의 공개 데이터셋에서 기존 방법(RP) 대비 분류 정확도 최대 6.14%, AUROC 최대 4.33% 향상시켰습니다.
출판물
  • 2024.12International Conference[pdf][link][code]
    Detecting Concept Shifts under Different Levels of Self-awareness on Emotion Labeling
    
27th International Conference on Pattern Recognition (ICPR 2024)
    Hyoseon Choi, Dahoon Choi, Netiwit Kaongeon, Byung Hyung Kim*
  • 2024.05Domestic Journal[pdf][link] 🏅KCC2023 우수논문상(인공지능분야) 초청논문 2023.06.19
    EEG 기반 감정 분류에서 MSP를 사용한 OOD 검출 적용
    
정보과학회논문지 (Journal of KIISE)
    최효선, 최다훈, 김병형*
  • 2024.02International Conference[pdf][link][code]
    Multi-Output Regression for Integrated Prediction of Valence and Arousal in EEG-Based Emotion Recognition
    
12th IEEE International Winter Conference on Brain-Computer Interface (WinterBCI)
    Hyoseon Choi, ChaeEun Woo, JiYun Kong, Byung Hyung Kim*
  • 2023.08International Journal[pdf][link]
    Decoding Auditory-Evoked Response in Affective States using Wearable Around-Ear EEG System
    
Biomedical Physics and Engineering Express
    
Jaehoon Choi, Netiwit Kaongoen, Hyoseon Choi, Minuk Kim, Byung Hyung Kim*, Sungho Jo*
기술 스택
언어PythonR | 딥러닝/MLPyTorchTensorFlowKerasscikit-learn | 데이터/시각화NumPyPandasSciPyMatplotlibSeaborn | 신호처리/통계MNEMATLABJamovi | 환경/도구JupyterGitLinux | CS정보처리기사2021.11.26 | 기타 경험HTMLCSSReactMongoDB
RAG Agent 구축LangChainLangGraphRAGChromaDB
기타경험
  • 영어 어학연수 호주, 브리즈번 2024.09.09—2025.09.19 | Greenwich English College 1년, Cambridge FCE B2 취득 2025.06.10
  • 국제 학회 포스터 발표 | ICPR 2024 인도, 콜카타 2024.12.01—2024.12.05
  • 공부한 책
연락처
Email
🇺🇸 English
Hi there 👋
Conducted AI research focused on EEG-based emotion modeling and data reliability.
Research to Product: Bridging the gap between lab-validated AI and AI that works in the real world.
AI Data Reliability · Domain-specific AI · Affective Computing
Education
Master's Thesis
Data Reliability in EEG-based Emotion Recognition: A Framework for Unreliable Data Pair Removal
Affective AI Lab | Advisor: Byung Hyung Kim
Proposed a data cleansing framework that identifies and removes unreliable EEG-label pairs — samples where the correlation between EEG signals and emotion labels is degraded — using deep learning-based Out-of-Distribution (OOD) detection. Achieved up to +6.14% improvement in classification accuracy and +4.33% in AUROC over the conventional method (Riemannian Potato) across three public datasets.
Publications
  • 2024.12International Conference[pdf][link][code]
    Detecting Concept Shifts under Different Levels of Self-awareness on Emotion Labeling
    
27th International Conference on Pattern Recognition (ICPR 2024)
    Hyoseon Choi, Dahoon Choi, Netiwit Kaongeon, Byung Hyung Kim*
  • 2024.05Domestic Journal[pdf][link] 🏅Invited from KCC 2023 Best Paper 2023.06.19
    Applying OOD Detection using MSP in EEG-based Emotion Classification
    
Journal of KIISE
    Hyoseon Choi, Dahoon Choi, Byung Hyung Kim*
  • 2024.02International Conference[pdf][link][code]
    Multi-Output Regression for Integrated Prediction of Valence and Arousal in EEG-Based Emotion Recognition
    
12th IEEE International Winter Conference on Brain-Computer Interface (WinterBCI)
    Hyoseon Choi, ChaeEun Woo, JiYun Kong, Byung Hyung Kim*
  • 2023.08International Journal[pdf][link]
    Decoding Auditory-Evoked Response in Affective States using Wearable Around-Ear EEG System
    
Biomedical Physics and Engineering Express
    
Jaehoon Choi, Netiwit Kaongoen, Hyoseon Choi, Minuk Kim, Byung Hyung Kim*, Sungho Jo*
Tech Stack
LanguagesPythonR | Deep Learning/MLPyTorchTensorFlowKerasscikit-learn | Data/VisualizationNumPyPandasSciPyMatplotlibSeaborn | Signal Processing/StatisticsMNEMATLABJamovi | Environment/ToolsJupyterGitLinux | CSEngineer Information Processing2021.11.26 | Other ExperienceHTMLCSSReactMongoDB
RAG AgentLangChainLangGraphRAGChromaDB
Experience
  • English Language Program Brisbane, Australia 2024.09.09—2025.09.19 | Greenwich English College, Cambridge FCE B2 2025.06.10
  • International Conference Poster Presentation | ICPR 2024 Kolkata, India 2024.12.01—2024.12.05
  • Books I've Studied
    • Deep Learning from Scratch 1, 2 — Inha Univ. AI Club AiDL Study
    • Machine Learning + Deep Learning by Yourself, Do It! Deep Learning, AI and ML for Coders in Pytorch/Laurence Moroney
Contact
Email

Pinned
Loading
  1. KoreanFashionKoreanFashionPublic
    Jupyter Notebook
  2. PyQt_TPMPyQt_TPMPublic
    Python
  3. affctivai/coglieraffctivai/coglierPublic
    
Detecting Concept Shifts under Different Levels of Self-awareness on Emotion Labeling

    Python
1

2

  4. affctivai/MORaffctivai/MORPublic
    
Multi-Output Regression for Integrated Prediction of Valence and Arousal in EEG-Based Emotion Recognition

    Jupyter Notebook
1

1

  5. algo-bojalgo-bojPublic
    Python
  6. fastapi-onnx-servingfastapi-onnx-servingPublic
    
Image classification API using FastAPI + ONNX Runtime (ResNet-18)

    HTML

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default");
}
} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
View HyoSeonChoi's full-sized avatar
1
follower
 · 7
following

Achievements
Achievement: YOLOAchievement: Pull Sharkx2
Achievements
Achievement: YOLOAchievement: Pull Sharkx2
Organizations
@affctivai

Block or report HyoSeonChoi

Block user

Prevent this user from interacting with your repositories and sending you notifications.
Learn more about blocking users.


You must be logged in to block users.


Content in all repositories owned by your account will be closed.


Maximum 250 characters. Please don’t include any personal information such as legal names or email addresses. Markdown is supported. This note will only be visible to you.

Report abuse

Contact GitHub support about this user’s behavior.
Learn more about reporting abuse.

Report abuse
HyoSeonChoi/README.md
🇰🇷 한국어
뇌파(EEG)와 감정 모델링을 중심으로 AI 연구를 수행했습니다.
Research to Product: 연구실 안에서 잘 되는 AI를 넘어, 실제 환경에서 쓰이는 AI로 나아가고자 합니다.
AI 데이터 신뢰성 · 도메인 기반 AI · 감성 컴퓨팅(Affective Computing)
학력
석사 논문
EEG 기반 감정 인식에서의 데이터 신뢰성 : 비신뢰 쌍 탐지 및 제거 프레임워크 개발
감성인공지능 연구실 | 지도교수님: 김병형
뇌파(EEG) 데이터와 감정 레이블 간 상관성이 저하된 데이터 샘플들을 딥러닝의 OOD(Out-of-Distribution) 탐지 기법으로 식별·제거하는 데이터 정제 프레임워크를 제안하였습니다. 세 개의 공개 데이터셋에서 기존 방법(RP) 대비 분류 정확도 최대 6.14%, AUROC 최대 4.33% 향상시켰습니다.
출판물
  • 2024.12International Conference[pdf][link][code]
    Detecting Concept Shifts under Different Levels of Self-awareness on Emotion Labeling
    
27th International Conference on Pattern Recognition (ICPR 2024)
    Hyoseon Choi, Dahoon Choi, Netiwit Kaongeon, Byung Hyung Kim*
  • 2024.05Domestic Journal[pdf][link] 🏅KCC2023 우수논문상(인공지능분야) 초청논문 2023.06.19
    EEG 기반 감정 분류에서 MSP를 사용한 OOD 검출 적용
    
정보과학회논문지 (Journal of KIISE)
    최효선, 최다훈, 김병형*
  • 2024.02International Conference[pdf][link][code]
    Multi-Output Regression for Integrated Prediction of Valence and Arousal in EEG-Based Emotion Recognition
    
12th IEEE International Winter Conference on Brain-Computer Interface (WinterBCI)
    Hyoseon Choi, ChaeEun Woo, JiYun Kong, Byung Hyung Kim*
  • 2023.08International Journal[pdf][link]
    Decoding Auditory-Evoked Response in Affective States using Wearable Around-Ear EEG System
    
Biomedical Physics and Engineering Express
    
Jaehoon Choi, Netiwit Kaongoen, Hyoseon Choi, Minuk Kim, Byung Hyung Kim*, Sungho Jo*
기술 스택
언어PythonR | 딥러닝/MLPyTorchTensorFlowKerasscikit-learn | 데이터/시각화NumPyPandasSciPyMatplotlibSeaborn | 신호처리/통계MNEMATLABJamovi | 환경/도구JupyterGitLinux | CS정보처리기사2021.11.26 | 기타 경험HTMLCSSReactMongoDB
RAG Agent 구축LangChainLangGraphRAGChromaDB
기타경험
  • 영어 어학연수 호주, 브리즈번 2024.09.09—2025.09.19 | Greenwich English College 1년, Cambridge FCE B2 취득 2025.06.10
  • 국제 학회 포스터 발표 | ICPR 2024 인도, 콜카타 2024.12.01—2024.12.05
  • 공부한 책
연락처
Email
🇺🇸 English
Hi there 👋
Conducted AI research focused on EEG-based emotion modeling and data reliability.
Research to Product: Bridging the gap between lab-validated AI and AI that works in the real world.
AI Data Reliability · Domain-specific AI · Affective Computing
Education
Master's Thesis
Data Reliability in EEG-based Emotion Recognition: A Framework for Unreliable Data Pair Removal
Affective AI Lab | Advisor: Byung Hyung Kim
Proposed a data cleansing framework that identifies and removes unreliable EEG-label pairs — samples where the correlation between EEG signals and emotion labels is degraded — using deep learning-based Out-of-Distribution (OOD) detection. Achieved up to +6.14% improvement in classification accuracy and +4.33% in AUROC over the conventional method (Riemannian Potato) across three public datasets.
Publications
  • 2024.12International Conference[pdf][link][code]
    Detecting Concept Shifts under Different Levels of Self-awareness on Emotion Labeling
    
27th International Conference on Pattern Recognition (ICPR 2024)
    Hyoseon Choi, Dahoon Choi, Netiwit Kaongeon, Byung Hyung Kim*
  • 2024.05Domestic Journal[pdf][link] 🏅Invited from KCC 2023 Best Paper 2023.06.19
    Applying OOD Detection using MSP in EEG-based Emotion Classification
    
Journal of KIISE
    Hyoseon Choi, Dahoon Choi, Byung Hyung Kim*
  • 2024.02International Conference[pdf][link][code]
    Multi-Output Regression for Integrated Prediction of Valence and Arousal in EEG-Based Emotion Recognition
    
12th IEEE International Winter Conference on Brain-Computer Interface (WinterBCI)
    Hyoseon Choi, ChaeEun Woo, JiYun Kong, Byung Hyung Kim*
  • 2023.08International Journal[pdf][link]
    Decoding Auditory-Evoked Response in Affective States using Wearable Around-Ear EEG System
    
Biomedical Physics and Engineering Express
    
Jaehoon Choi, Netiwit Kaongoen, Hyoseon Choi, Minuk Kim, Byung Hyung Kim*, Sungho Jo*
Tech Stack
LanguagesPythonR | Deep Learning/MLPyTorchTensorFlowKerasscikit-learn | Data/VisualizationNumPyPandasSciPyMatplotlibSeaborn | Signal Processing/StatisticsMNEMATLABJamovi | Environment/ToolsJupyterGitLinux | CSEngineer Information Processing2021.11.26 | Other ExperienceHTMLCSSReactMongoDB
RAG AgentLangChainLangGraphRAGChromaDB
Experience
  • English Language Program Brisbane, Australia 2024.09.09—2025.09.19 | Greenwich English College, Cambridge FCE B2 2025.06.10
  • International Conference Poster Presentation | ICPR 2024 Kolkata, India 2024.12.01—2024.12.05
  • Books I've Studied
    • Deep Learning from Scratch 1, 2 — Inha Univ. AI Club AiDL Study
    • Machine Learning + Deep Learning by Yourself, Do It! Deep Learning, AI and ML for Coders in Pytorch/Laurence Moroney
Contact
Email

Pinned
Loading
  1. KoreanFashionKoreanFashionPublic
    Jupyter Notebook
  2. PyQt_TPMPyQt_TPMPublic
    Python
  3. affctivai/coglieraffctivai/coglierPublic
    
Detecting Concept Shifts under Different Levels of Self-awareness on Emotion Labeling

    Python
1

2

  4. affctivai/MORaffctivai/MORPublic
    
Multi-Output Regression for Integrated Prediction of Valence and Arousal in EEG-Based Emotion Recognition

    Jupyter Notebook
1

1

  5. algo-bojalgo-bojPublic
    Python
  6. fastapi-onnx-servingfastapi-onnx-servingPublic
    
Image classification API using FastAPI + ONNX Runtime (ResNet-18)

    HTML

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers");
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
View HyoSeonChoi's full-sized avatar
1
follower
 · 7
following

Achievements
Achievement: YOLOAchievement: Pull Sharkx2
Achievements
Achievement: YOLOAchievement: Pull Sharkx2
Organizations
@affctivai

Block or report HyoSeonChoi

Block user

Prevent this user from interacting with your repositories and sending you notifications.
Learn more about blocking users.


You must be logged in to block users.


Content in all repositories owned by your account will be closed.


Maximum 250 characters. Please don’t include any personal information such as legal names or email addresses. Markdown is supported. This note will only be visible to you.

Report abuse

Contact GitHub support about this user’s behavior.
Learn more about reporting abuse.

Report abuse
HyoSeonChoi/README.md
🇰🇷 한국어
뇌파(EEG)와 감정 모델링을 중심으로 AI 연구를 수행했습니다.
Research to Product: 연구실 안에서 잘 되는 AI를 넘어, 실제 환경에서 쓰이는 AI로 나아가고자 합니다.
AI 데이터 신뢰성 · 도메인 기반 AI · 감성 컴퓨팅(Affective Computing)
학력
석사 논문
EEG 기반 감정 인식에서의 데이터 신뢰성 : 비신뢰 쌍 탐지 및 제거 프레임워크 개발
감성인공지능 연구실 | 지도교수님: 김병형
뇌파(EEG) 데이터와 감정 레이블 간 상관성이 저하된 데이터 샘플들을 딥러닝의 OOD(Out-of-Distribution) 탐지 기법으로 식별·제거하는 데이터 정제 프레임워크를 제안하였습니다. 세 개의 공개 데이터셋에서 기존 방법(RP) 대비 분류 정확도 최대 6.14%, AUROC 최대 4.33% 향상시켰습니다.
출판물
  • 2024.12International Conference[pdf][link][code]
    Detecting Concept Shifts under Different Levels of Self-awareness on Emotion Labeling
    
27th International Conference on Pattern Recognition (ICPR 2024)
    Hyoseon Choi, Dahoon Choi, Netiwit Kaongeon, Byung Hyung Kim*
  • 2024.05Domestic Journal[pdf][link] 🏅KCC2023 우수논문상(인공지능분야) 초청논문 2023.06.19
    EEG 기반 감정 분류에서 MSP를 사용한 OOD 검출 적용
    
정보과학회논문지 (Journal of KIISE)
    최효선, 최다훈, 김병형*
  • 2024.02International Conference[pdf][link][code]
    Multi-Output Regression for Integrated Prediction of Valence and Arousal in EEG-Based Emotion Recognition
    
12th IEEE International Winter Conference on Brain-Computer Interface (WinterBCI)
    Hyoseon Choi, ChaeEun Woo, JiYun Kong, Byung Hyung Kim*
  • 2023.08International Journal[pdf][link]
    Decoding Auditory-Evoked Response in Affective States using Wearable Around-Ear EEG System
    
Biomedical Physics and Engineering Express
    
Jaehoon Choi, Netiwit Kaongoen, Hyoseon Choi, Minuk Kim, Byung Hyung Kim*, Sungho Jo*
기술 스택
언어PythonR | 딥러닝/MLPyTorchTensorFlowKerasscikit-learn | 데이터/시각화NumPyPandasSciPyMatplotlibSeaborn | 신호처리/통계MNEMATLABJamovi | 환경/도구JupyterGitLinux | CS정보처리기사2021.11.26 | 기타 경험HTMLCSSReactMongoDB
RAG Agent 구축LangChainLangGraphRAGChromaDB
기타경험
  • 영어 어학연수 호주, 브리즈번 2024.09.09—2025.09.19 | Greenwich English College 1년, Cambridge FCE B2 취득 2025.06.10
  • 국제 학회 포스터 발표 | ICPR 2024 인도, 콜카타 2024.12.01—2024.12.05
  • 공부한 책
연락처
Email
🇺🇸 English
Hi there 👋
Conducted AI research focused on EEG-based emotion modeling and data reliability.
Research to Product: Bridging the gap between lab-validated AI and AI that works in the real world.
AI Data Reliability · Domain-specific AI · Affective Computing
Education
Master's Thesis
Data Reliability in EEG-based Emotion Recognition: A Framework for Unreliable Data Pair Removal
Affective AI Lab | Advisor: Byung Hyung Kim
Proposed a data cleansing framework that identifies and removes unreliable EEG-label pairs — samples where the correlation between EEG signals and emotion labels is degraded — using deep learning-based Out-of-Distribution (OOD) detection. Achieved up to +6.14% improvement in classification accuracy and +4.33% in AUROC over the conventional method (Riemannian Potato) across three public datasets.
Publications
  • 2024.12International Conference[pdf][link][code]
    Detecting Concept Shifts under Different Levels of Self-awareness on Emotion Labeling
    
27th International Conference on Pattern Recognition (ICPR 2024)
    Hyoseon Choi, Dahoon Choi, Netiwit Kaongeon, Byung Hyung Kim*
  • 2024.05Domestic Journal[pdf][link] 🏅Invited from KCC 2023 Best Paper 2023.06.19
    Applying OOD Detection using MSP in EEG-based Emotion Classification
    
Journal of KIISE
    Hyoseon Choi, Dahoon Choi, Byung Hyung Kim*
  • 2024.02International Conference[pdf][link][code]
    Multi-Output Regression for Integrated Prediction of Valence and Arousal in EEG-Based Emotion Recognition
    
12th IEEE International Winter Conference on Brain-Computer Interface (WinterBCI)
    Hyoseon Choi, ChaeEun Woo, JiYun Kong, Byung Hyung Kim*
  • 2023.08International Journal[pdf][link]
    Decoding Auditory-Evoked Response in Affective States using Wearable Around-Ear EEG System
    
Biomedical Physics and Engineering Express
    
Jaehoon Choi, Netiwit Kaongoen, Hyoseon Choi, Minuk Kim, Byung Hyung Kim*, Sungho Jo*
Tech Stack
LanguagesPythonR | Deep Learning/MLPyTorchTensorFlowKerasscikit-learn | Data/VisualizationNumPyPandasSciPyMatplotlibSeaborn | Signal Processing/StatisticsMNEMATLABJamovi | Environment/ToolsJupyterGitLinux | CSEngineer Information Processing2021.11.26 | Other ExperienceHTMLCSSReactMongoDB
RAG AgentLangChainLangGraphRAGChromaDB
Experience
  • English Language Program Brisbane, Australia 2024.09.09—2025.09.19 | Greenwich English College, Cambridge FCE B2 2025.06.10
  • International Conference Poster Presentation | ICPR 2024 Kolkata, India 2024.12.01—2024.12.05
  • Books I've Studied
    • Deep Learning from Scratch 1, 2 — Inha Univ. AI Club AiDL Study
    • Machine Learning + Deep Learning by Yourself, Do It! Deep Learning, AI and ML for Coders in Pytorch/Laurence Moroney
Contact
Email

Pinned
Loading
  1. KoreanFashionKoreanFashionPublic
    Jupyter Notebook
  2. PyQt_TPMPyQt_TPMPublic
    Python
  3. affctivai/coglieraffctivai/coglierPublic
    
Detecting Concept Shifts under Different Levels of Self-awareness on Emotion Labeling

    Python
1

2

  4. affctivai/MORaffctivai/MORPublic
    
Multi-Output Regression for Integrated Prediction of Valence and Arousal in EEG-Based Emotion Recognition

    Jupyter Notebook
1

1

  5. algo-bojalgo-bojPublic
    Python
  6. fastapi-onnx-servingfastapi-onnx-servingPublic
    
Image classification API using FastAPI + ONNX Runtime (ResNet-18)

    HTML

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode");
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();

Skip to content
View HyoSeonChoi's full-sized avatar
1
follower
 · 7
following

Achievements
Achievement: YOLOAchievement: Pull Sharkx2
Achievements
Achievement: YOLOAchievement: Pull Sharkx2
Organizations
@affctivai

Block or report HyoSeonChoi

Block user

Prevent this user from interacting with your repositories and sending you notifications.
Learn more about blocking users.


You must be logged in to block users.


Content in all repositories owned by your account will be closed.


Maximum 250 characters. Please don’t include any personal information such as legal names or email addresses. Markdown is supported. This note will only be visible to you.

Report abuse

Contact GitHub support about this user’s behavior.
Learn more about reporting abuse.

Report abuse
HyoSeonChoi/README.md
🇰🇷 한국어
뇌파(EEG)와 감정 모델링을 중심으로 AI 연구를 수행했습니다.
Research to Product: 연구실 안에서 잘 되는 AI를 넘어, 실제 환경에서 쓰이는 AI로 나아가고자 합니다.
AI 데이터 신뢰성 · 도메인 기반 AI · 감성 컴퓨팅(Affective Computing)
학력
석사 논문
EEG 기반 감정 인식에서의 데이터 신뢰성 : 비신뢰 쌍 탐지 및 제거 프레임워크 개발
감성인공지능 연구실 | 지도교수님: 김병형
뇌파(EEG) 데이터와 감정 레이블 간 상관성이 저하된 데이터 샘플들을 딥러닝의 OOD(Out-of-Distribution) 탐지 기법으로 식별·제거하는 데이터 정제 프레임워크를 제안하였습니다. 세 개의 공개 데이터셋에서 기존 방법(RP) 대비 분류 정확도 최대 6.14%, AUROC 최대 4.33% 향상시켰습니다.
출판물
  • 2024.12International Conference[pdf][link][code]
    Detecting Concept Shifts under Different Levels of Self-awareness on Emotion Labeling
    
27th International Conference on Pattern Recognition (ICPR 2024)
    Hyoseon Choi, Dahoon Choi, Netiwit Kaongeon, Byung Hyung Kim*
  • 2024.05Domestic Journal[pdf][link] 🏅KCC2023 우수논문상(인공지능분야) 초청논문 2023.06.19
    EEG 기반 감정 분류에서 MSP를 사용한 OOD 검출 적용
    
정보과학회논문지 (Journal of KIISE)
    최효선, 최다훈, 김병형*
  • 2024.02International Conference[pdf][link][code]
    Multi-Output Regression for Integrated Prediction of Valence and Arousal in EEG-Based Emotion Recognition
    
12th IEEE International Winter Conference on Brain-Computer Interface (WinterBCI)
    Hyoseon Choi, ChaeEun Woo, JiYun Kong, Byung Hyung Kim*
  • 2023.08International Journal[pdf][link]
    Decoding Auditory-Evoked Response in Affective States using Wearable Around-Ear EEG System
    
Biomedical Physics and Engineering Express
    
Jaehoon Choi, Netiwit Kaongoen, Hyoseon Choi, Minuk Kim, Byung Hyung Kim*, Sungho Jo*
기술 스택
언어PythonR | 딥러닝/MLPyTorchTensorFlowKerasscikit-learn | 데이터/시각화NumPyPandasSciPyMatplotlibSeaborn | 신호처리/통계MNEMATLABJamovi | 환경/도구JupyterGitLinux | CS정보처리기사2021.11.26 | 기타 경험HTMLCSSReactMongoDB
RAG Agent 구축LangChainLangGraphRAGChromaDB
기타경험
  • 영어 어학연수 호주, 브리즈번 2024.09.09—2025.09.19 | Greenwich English College 1년, Cambridge FCE B2 취득 2025.06.10
  • 국제 학회 포스터 발표 | ICPR 2024 인도, 콜카타 2024.12.01—2024.12.05
  • 공부한 책
연락처
Email
🇺🇸 English
Hi there 👋
Conducted AI research focused on EEG-based emotion modeling and data reliability.
Research to Product: Bridging the gap between lab-validated AI and AI that works in the real world.
AI Data Reliability · Domain-specific AI · Affective Computing
Education
Master's Thesis
Data Reliability in EEG-based Emotion Recognition: A Framework for Unreliable Data Pair Removal
Affective AI Lab | Advisor: Byung Hyung Kim
Proposed a data cleansing framework that identifies and removes unreliable EEG-label pairs — samples where the correlation between EEG signals and emotion labels is degraded — using deep learning-based Out-of-Distribution (OOD) detection. Achieved up to +6.14% improvement in classification accuracy and +4.33% in AUROC over the conventional method (Riemannian Potato) across three public datasets.
Publications
  • 2024.12International Conference[pdf][link][code]
    Detecting Concept Shifts under Different Levels of Self-awareness on Emotion Labeling
    
27th International Conference on Pattern Recognition (ICPR 2024)
    Hyoseon Choi, Dahoon Choi, Netiwit Kaongeon, Byung Hyung Kim*
  • 2024.05Domestic Journal[pdf][link] 🏅Invited from KCC 2023 Best Paper 2023.06.19
    Applying OOD Detection using MSP in EEG-based Emotion Classification
    
Journal of KIISE
    Hyoseon Choi, Dahoon Choi, Byung Hyung Kim*
  • 2024.02International Conference[pdf][link][code]
    Multi-Output Regression for Integrated Prediction of Valence and Arousal in EEG-Based Emotion Recognition
    
12th IEEE International Winter Conference on Brain-Computer Interface (WinterBCI)
    Hyoseon Choi, ChaeEun Woo, JiYun Kong, Byung Hyung Kim*
  • 2023.08International Journal[pdf][link]
    Decoding Auditory-Evoked Response in Affective States using Wearable Around-Ear EEG System
    
Biomedical Physics and Engineering Express
    
Jaehoon Choi, Netiwit Kaongoen, Hyoseon Choi, Minuk Kim, Byung Hyung Kim*, Sungho Jo*
Tech Stack
LanguagesPythonR | Deep Learning/MLPyTorchTensorFlowKerasscikit-learn | Data/VisualizationNumPyPandasSciPyMatplotlibSeaborn | Signal Processing/StatisticsMNEMATLABJamovi | Environment/ToolsJupyterGitLinux | CSEngineer Information Processing2021.11.26 | Other ExperienceHTMLCSSReactMongoDB
RAG AgentLangChainLangGraphRAGChromaDB
Experience
  • English Language Program Brisbane, Australia 2024.09.09—2025.09.19 | Greenwich English College, Cambridge FCE B2 2025.06.10
  • International Conference Poster Presentation | ICPR 2024 Kolkata, India 2024.12.01—2024.12.05
  • Books I've Studied
    • Deep Learning from Scratch 1, 2 — Inha Univ. AI Club AiDL Study
    • Machine Learning + Deep Learning by Yourself, Do It! Deep Learning, AI and ML for Coders in Pytorch/Laurence Moroney
Contact
Email

Pinned
Loading
  1. KoreanFashionKoreanFashionPublic
    Jupyter Notebook
  2. PyQt_TPMPyQt_TPMPublic
    Python
  3. affctivai/coglieraffctivai/coglierPublic
    
Detecting Concept Shifts under Different Levels of Self-awareness on Emotion Labeling

    Python
1

2

  4. affctivai/MORaffctivai/MORPublic
    
Multi-Output Regression for Integrated Prediction of Valence and Arousal in EEG-Based Emotion Recognition

    Jupyter Notebook
1

1

  5. algo-bojalgo-bojPublic
    Python
  6. fastapi-onnx-servingfastapi-onnx-servingPublic
    
Image classification API using FastAPI + ONNX Runtime (ResNet-18)

    HTML