(Including but not limited to the following topics)
Track 1: Computer Vision
Image Processing
Data Visualization
Big Data and Computer Vision
Biometric Recognition
Biomedical Image Analysis
Remote Sensing Images
Computational Photography
Object Detection Algorithms
Sensing and Display
Data Sets and Performance Analysis
Deep Learning in Computer Vision
Machine Vision Technology
Machine Learning
Computer Graphics
Biological Vision
Modeling of Natural Scenes and Phenomena
Machine Engines for Graphics and VR
Track 2: Neural Networks
Robot Control
Optimization and Combination
Knowledge Engineering Artificial Intelligence
Logical programming design
Human-computer interaction
Deep learning
Signal processing
Information extraction
Natural language inference
Track 3: Deep Learning
Deep learning basic algorithms
Deep learning in computer vision
Combination of natural language processing and vision
Transfer learning
Domain adaptation
Reinforcement learning
Joint learning and privacy protection
Self-supervised and unsupervised learning
Interpretability of deep learning models
Edge computing