📚︎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