Showing 1–20 of 21 results
/ Date/ Name
Dec 2, 2025SMP: Reusable Score-Matching Motion Priors for Physics-Based Character ControlOct 17, 2025SHARE: Scene-Human Aligned ReconstructionMay 6, 2025StableMotion: Training Motion Cleanup Models with Unpaired Corrupted DataSep 3, 2024MetaFood3D: 3D Food Dataset with Nutrition ValuesMay 13, 2024NutritionVerse-Direct: Exploring Deep Neural Networks for Multitask Nutrition Prediction from Food ImagesMay 12, 2024In The Wild Ellipse Parameter Estimation for Circular Dining Plates and BowlsMay 12, 2024How Much You Ate? Food Portion Estimation on SpoonsSep 14, 2023NutritionVerse: Empirical Study of Various Dietary Intake Estimation ApproachesJun 15, 2023Transferring Knowledge for Food Image Segmentation using Transformers and ConvolutionsApr 12, 2023NutritionVerse-Thin: An Optimized Strategy for Enabling Improved Rendering of 3D Thin Food ModelsApr 12, 2023NutritionVerse-3D: A 3D Food Model Dataset for Nutritional Intake EstimationJan 4, 2023COVID-Net USPro: An Open-Source Explainable Few-Shot Deep Prototypical Network to Monitor and Detect COVID-19 Infection from Point-of-Care Ultrasound ImagesDec 6, 2022A Trustworthy Framework for Medical Image Analysis with Deep LearningJul 19, 2022Towards Trustworthy Healthcare AI: Attention-Based Feature Learning for COVID-19 Screening With Chest RadiographyMay 18, 2022COVID-Net UV: An End-to-End Spatio-Temporal Deep Neural Network Architecture for Automated Diagnosis of COVID-19 Infection from Ultrasound VideosDec 14, 2021Performance or Trust? Why Not Both. Deep AUC Maximization with Self-Supervised Learning for COVID-19 Chest X-ray ClassificationsAug 5, 2021COVID-Net US: A Tailored, Highly Efficient, Self-Attention Deep Convolutional Neural Network Design for Detection of COVID-19 Patient Cases from Point-of-care Ultrasound ImagingMay 4, 2021COVID-19 Detection from Chest X-ray Images using Imprinted Weights ApproachMar 18, 2021COVIDx-US -- An open-access benchmark dataset of ultrasound imaging data for AI-driven COVID-19 analyticsJul 22, 2020Understanding the temporal evolution of COVID-19 research through machine learning and natural language processing