◕ Track 1: AI & Machine Learning Methods

Machine Learning Methods and Applications

Deep Learning and Reinforcement Learning

Neural Networks

Computational Learning Theory

Optimization of AI/ML Methods

Pattern Recognition and Classification

Data Mining and Knowledge Discovery

Hybrid Intelligent Systems

Soft Computing Theory and Applications

Experimental Evaluation of AI/ML Algorithms

Distributed and Parallel AI/ML Algorithms

Algorithmic Tools for AI/ML

◕ Track 2: Intelligent Systems and Applied Machine Learning

Computer Vision and Image Understanding

Signal and Image Processing

AI/ML Applications in Vision and Imaging

Natural Language Processing

Speech and Language Processing

AI/ML Applications in NLP and Speech

Multimedia Analysis and Cognitive Informatics

AI-based Intelligent System Architectures

Robotics and Intelligent Automation

Applied Machine Learning for Intelligent Manufacturing

Machine Learning Methods for Network Optimization

Machine Learning for Internet of Things

Security and Privacy of AI/ML Systems

Experimental Evaluation and Deployment of AI/ML Applications