China
Displaying present location in the site.
Vision AI
ML research team is committed to cutting-edge and applied research related to computational vision. Main research achievements include:
- Developed uncertainty inference tech for state-of-the-art deep models to deliver highly reliable AI systems
- Developed data-efficient learning tech (Data Refiner) for addressing the challenge of data and label defects, and achieved AI-enabled process automation to deliver high quality AI training data
- In-depth collaboration with leading hospitals in medical diagnosis AI, and developed Endowise® endoscopy quality control system that obtained medical device registry (京械注准20232210470) and was applied in clinical practice
Current Research Focuses：
- Deliver high-accuracy video analysis unit technologies for pedestrian & object detecting and tracking in complex public spaces, realizing real-time digitization and visualization of human activity
- Synthesize images and simulate virtual environments to enhance the accuracy, robustness, and effectiveness of video analysis systems
Video Analysis
Human & object tracking
ReID retrieval
Human & object association
Image Recognition
Attribute analysis
Pose & action recognition
People & vehicle counting
Publication
- 【ISBI 2021】UNCERTAINTY-GUIDED ROBUST TRAINING FOR MEDICAL IMAGE SEGMENTATION
- 【IJCNN 2021 (Accepted)】Model Performance Inspection of Deep Neural Networks by Decomposing Bayesian Uncertainty Estimates
- 【IJCNN 2021 (Accepted)】Layerwise Approximate Inference for Bayesian Uncertainty Estimates on Deep Neural Networks
- 【MICCAI 2020】An Effective Data Refinement Approach for Upper Gastrointestinal Anatomy Recognition
- 【ICIP 2020】Loss Rescaling by Uncertainty Inference for Single-stage Object Detection
- 【IJCNN 2020】A Layer-wise Adversarial Training Approach to Improve Adversarial Robustness