📚︎Track 1: Pattern Recognition & Machine Learning

Supervised, unsupervised, and semi-supervised learning

Deep learning architectures and theory

Transfer learning and domain adaptation

Meta-learning and few-shot learning

Generative models and adversarial learning

Graph neural networks and relational learning

Representation learning and feature extraction

Dimensionality reduction and manifold learning

Ensemble methods and model fusion

Interpretable and explainable AI

Probabilistic reasoning and Bayesian methods

Reinforcement learning and sequential decision-making

Online and incremental learning

Large-scale and distributed machine learning

Benchmarking, evaluation, and performance analysis 

📚︎Track 2: Computer Vision & Multimodal Analysis

Image and video processing

Object detection, recognition, and tracking

Scene understanding and semantic segmentation

3D vision and reconstruction

Motion analysis and optical flow

Face, gesture, and human pose estimation

Facial expression and emotion recognition

Action and activity recognition

Multimodal learning and cross-modal retrieval

Vision-language models and grounding

Document analysis and optical character recognition

Medical image analysis and diagnosis

Remote sensing and aerial image interpretation

Real-time and embedded vision systems

Synthetic data and data augmentation for vision

📚︎Track 3: Speech, Language, and Multimodal Intelligence

Speech recognition and synthesis 

Speaker recognition and diarization 

Natural language understanding and generation

Machine translation and multilingual processing 

Text classification, summarization, and question answering

Sentiment analysis and opinion mining 

Knowledge representation and information extraction 

Dialogue systems and conversational AI 

Large language models and fine-tuning strategies 

Multimodal sentiment and emotion analysis 

Audio-visual speech processing

Cross-lingual and low-resource NLP 

Semantic parsing and reasoning 

Fact-checking, faithfulness, and hallucination mitigation 

Human-computer interaction and intelligent interfaces 

📚︎Track 4: Pattern Mining and Knowledge Discovery from Data

Clustering, classification, and anomaly pattern detection

Sequential and temporal pattern recognition

Spatiotemporal pattern mining and analysis 

Graph structure and network pattern analysis 

Causal pattern discovery and inference 

Pattern discovery via multi-source data fusion 

Feature learning and selection for high-dimensional data

User behavior pattern modeling and recommender systems 

Pattern evolution and change point detection 

Imbalanced learning and rare pattern recognition 

Transferable and cross-domain pattern discovery

Interpretable pattern mining and visualization 

Data preprocessing and quality enhancement for pattern analysis 

Large-scale and distributed pattern mining 

Privacy-preserving pattern recognition and mining