HOME > CALL FOR PAPER

Papers describing original work, as shown in any topic below, are invited. Acceptance will be based on quality, relevance, originality, etc. Both full research and work-in-progress reports are welcome. Topics of interest for submission include, but are not limited to:

Track 1: Artificial Intelligence

AI Algorithms
Natural Language Processing
Fuzzy Logic
Computer Vision and Image Understanding
Signal and Image Processing
Speech and Natural Language Processing
Computational Theories of Learning
Information Retrieval and Fusion
Hybrid Intelligent Systems
Intelligent System Architectures
Knowledge Representation
Knowledge-based Systems
Mechatronics

Multimedia & Cognitive Informatics
Parallel Processing
Pattern Recognition
Pervasive Computing and Ambient Intelligence
Soft Computing Theory and Applications
Software & Hardware Architectures
Automatic Programming
Machine Learning
Automatic Control
Data Mining and Machine Learning Tools
Robotics
Artificial Intelligence Tools & Application
Recent Trends and Developments

Track 2: Deep Learning

Neuro-Fuzzy Algorithms
Evolutionary Methods
Convolutional Neural Networks (CNN)
Deep Hierarchical Networks (DHN)
Unsupervised Feature Learning
Deep Boltzmann Machines
Generative Adversarial Networks (GAN)
Deep Metric Learning Methods
Deep Reinforcement Learning
Learning Deep Generative Models
Graph Representation Learning

Active learning
Agent-based learning
Manifold learning
Multi-task learning
Statistical models and learning
Computational learning
Evolutionary algorithms and learning
Fuzzy logic-based learning
Parallel and distributed learning
Deep Learning for Computing and Network Platforms

Track 3: Neural Networks

Convolutional neural networks
Hebbian theory
Long short term memory
Residual neural networks
Self-organizing feature maps
Biological neural networks
Cellular neural networks
Feedforward neural networks
Extreme learning machines

Multilayer perceptions
Graph neural networks
Multi-layer neural network
Neural network hardware
Radial basis function networks
Recurrent neural networks
Hopfield neural networks