2026 International Conference on Human-Computer Interaction, Neural Networks and Deep Learning provides a premier forum for the presentation of new advances and research results in the fields of Human-Computer Interaction, Neural Networks and Deep Learning. The conference will bring together leading researchers, social workers and scientists in the domain of interest from around the world.
The topics of interest for submission include, but are not limited to:
◕ Man-Machine Interaction
· Artificial Intelligence
· Knowledge-augmented methods
· Multi-task learning
· Self-supervised learning
· Contrastive learning
· Generation model
· Data augmentation
· Word embedding
· Structured prediction
· Transfer learning / domain adaptation
· Representation learning
· Generalization
· Model compression methods
· Parameter-efficient finetuning
· Few-shot learning
· Reinforcement learning
· Optimization methods
· Continual learning
· Adversarial training
· Meta learning
· Causality
· Graphical models
· Human-in-a-loop / Active learning
◕ Neural Network
· Deep learning algorithm and its application
· Application of Convolutional Neural Network ( CNN ) in Image Processing
· Recurrent neural network ( RNN ) and its application in sequence data
· Autoencoder and generation model
· The application of neural network in natural language processing ( NLP )
· Application of Neural Network in Medical Image Analysis
· Application of neural network in bioinformatics
· Application of Neural Network in Intelligent Transportation System
· Application of neural network in robot control
· Application of Neural Network in Recommendation System
· Application of neural network in anomaly detection and early warning
· Federated learning and distributed neural networks
· Hardware acceleration of neural networks
· Application of Neural Network in Internet of Things ( IoT )
· Application of neural network in edge computing
· Neural Networks and Photonics
◕ Deep Learning
· Deep Learning Basic Algorithms
· Deep Learning in Computer Vision
· Natural Language Processing combined with Vision
· Migration Learning
· Domain Adaptation
· Augmented Learning
· Federated Learning and Privacy Preservation
· Self-supervised vs. unsupervised learning
· Deep Learning Model Interpretability
· Edge Computing