| 11/11 | MS | DroidEvolver: Self-Evolving Android Malware Detection System |
| 16/09 | MY | Machine Learning For Automatic Malware Representation and Analysis (PhD thesis) |
| 5/8 | AA | MRI Augmentation via Elastic Registration for Brain Lesions Segmentation |
| 22/7 | SS | Deep Supervised Cross-Modal Retrieval |
| 8/7 | MS | Improving Robustness of ML Classifiers against Realizable Evasion Attacks Using Conserved Features |
| 11/6 | WK | Overview of Biometrics and Medical Imaging for Machine Vision (Presentation) |
| 27/5 | ON | Discriminability Objective for Training Descriptive Captions |
| 13/5 | SS | Field guide for Troubleshooting Deep Neural Networks |
| 29/4 | MG | 3D MRI brain tumor segmentation using autoencoder regularization |
| 25/3 | AA | SegAN: Adversarial Network with Multi-scale L1 Loss for Medical Image Segmentation |
| 11/3 | XD | Deep Learning for MR Angiography: Automated Detection of Cerebral Aneurysms |
| 25/2 | SS | Diverse and Coherent Paragraph Generation from Images |
| 11/2 | MY | Neural Cleanse: Identifying and Mitigating Backdoor Attacks in Neural Networks |
| 2018 | | |
| 17/12 | LH | 30+ Years: A Research Story |
| 3/12 | TH | MRes Thesis on Convolutional Neural Networks for Prostate Magnetic Resonance Image Segmentation |
| 26/11 | RN | Machine learning with synthetic data - Sources: 1-Training Deep Networks with Synthetic Data: Bridging the Reality Gap by Domain Randomization, 2- Total Capture: A 3D Deformation Model for Tracking Faces, Hands, and Bodies and 3- Designing Empirical Lab Experiments for SAR-ATR |
| 19/11 | RN | MRes Thesis on Radar Emitter Recognition (RER) |
| 12/11 | LH | A. Zamir et alTaskonomy: Disentangling Task Transfer Learning |
| 29/10 | MS | P.Samangouei et alDefense-GAN: Protecting Classifiers Against Adversarial Attacks Using Generative Models |
| 22/10 | LW | Learning SPD-matrix-based Representation for Visual Recognition (Presentation) |
| 15/10 | AA | VoxResNet: Deep Voxelwise Residual Networks for Volumetric Brain Segmentation |
| 17/9 | MY | M. Peters et alDeep Contextualized word representations |
| 10/9 | SS | Rajpurkar et alCheXNet: Radiologist-Level Pneumonia Detection on Chest X-rays with Deep Learning |
| 3/9 | MS | M . Jagielski et alManipulating Machine Learning: Poisoning Attacks and Countermeasures for Regression Learning |
| 27/8 | Video | Nando de Freitas and Scott Reed Deep Learning: Practice and Trends (NIPS 2017 Tutorial) |
| 20/8 | YQ | Computer simulation for the vascular diseases, Where we are and where to go |
| 13/8 | MY | M. Zaheer et alDeep Sets |
| 6/8 | AA | N. Ballas et alDelving Deeper Into Convolutional Networks For Learning Video Representations |
| 30/7 | SS | A. Gordo and D. Larlus Beyond instance-level image retrieval: Leveraging captions to learn a global visual representation for semantic retrieval (Presentation) |
| 23/7 | MS | N. Papernot et alPractical Black-Box Attacks against Machine Learning |
| 9/7 | AA | Fast ai workshop session |
| 2/7 | WR | Modulating and decoding visual information: from cannabinoids to artificial neural networks |
| 25/6 | KS | Medical Imaging at Biomedical Informatics Group, CSRIO Health & Biosecurity (Presentation) |
| 18/6 | TH | H. Jia et alAtlas registration and ensemble deep convolutional neural network-based prostate segmentation using magnetic resonance imaging (Presentation) |
| 4/6 | PA | Vision and Language Learning: From Image Captioning and Visual Question Answering towards Embodied Agents (Details) |
| 28/5 | Video | Tom Goldstein What do Neural loss surfaces look like? |
| 21/5 | KH | A Radiologist's Introduction to Medical Imaging (Presentation) |
| 14/5 | SA | Impact of MRI technology on Alzheimer’s disease detection (Presentation) |
| 7/5 | SS | P. Wang et alFVQA: Fact-based Visual Question Answering |
| 30/4 | AA | J. Wolterink et alGenerative Adversarial Networks for Noise Reduction in Low-Dose CT |
| 23/4 | ON | Facial Expression Recognition using Deep Learning (Presentation) |
| 9/4 | MS | H. Qin et alDeepFish: Accurate underwater live fish recognition with a deep architecture |
| 26/3 | RN | Z. Yang et alHybrid Radar Emitter Recognition Based on Rough k-Means Classifier and Relevance Vector Machine (Presentation; RVM paper by Tipping) |
| 19/3 | MY | Yousefi-Azar et alMalytics: A Malware Detection Scheme |
| 12/3 | TH | Jegou et alThe One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic Segmentation (Presentation) |
| 26/2 | SA | Liu et alRelationship Induced Multi-Template Learning for Diagnosis of Alzheimer's Disease and Mild Cognitive Impairment |
| 5/2 | SS | Zhang et alMDNet: A Semantically and Visually Interpretable Medical Image Diagnosis Network (Resources) |