(Including but not limited to the following topics)
Track 1: Intelligent Computing
Intelligent Planning
Visual/Linguistic Perception
Evolutionary and Swarm Algorithms
Univariate Derivative-Free Optimization Algorithms
Fuzzy Sets and Fuzzy Logic
Hybridization of Intelligent Models/Algorithms Intelligent Search
Evolutionary computing, social computing, neural computing
Particle swarm algorithm, genetic algorithm
Simulated annealing algorithm
Computational geometry
Applications of computing technology and high-performance computing science
Software development for numerical computing
Fuzzy mathematics and mathematical logic
Graph theory and combinatorial algorithms, etc.
Track 2: Deep Learning
Basics of deep learning 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
Intelligent environment perception
Automated computing
Language translation, computer games, image processing
Track 3: Computer Vision
Big data and computer vision
Biometric recognition
Biomedical image analysis
Remote sensing images
Computational photography
Object detection algorithms
Sensing and display
Datasets and performance analysis
Deep learning in computer vision ......