Topics of interest for each track include (but are not limited to):
Track 1: Machine and Deep learning
- Ambient intelligence
- Big Data Visualization
- Blockchains
- Cognitive intelligence
- Cloud computing
- Cellular computing
- Complex Systems
- Deep learning
- Expert Systems
- Feature Elicitation
- Game AI
- Image Classification
- Intelligent Systems
- Knowledge Representation,
- Learning theory
- Multitasking and Transfer Learning
- Natural Language Processing
- Neural Networks and applications
- Probabilistic Reasoning
- Recommender Systems
- Reinforcement Learning
- Real-time Decisions
- Supervised Learning
- System Interpretability
- Semantic Analysis
- Structure Discovery
- Unsupervised Learning
Track 2: Computational Intelligence
- Combinatorial and numerical optimization
- Differential Evolution
- Evolutionary computing
- Fuzzy systems
- Fuzzy Quadratic programming
- Genetic Algorithm
- Genetic Programming
- Gene Expression
- Multi criteria decision making
- Nature Inspired Computing
- Natural Heuristic Methods
- Nature-inspired metaheuristic algorithms
- Rough Sets
- Soft Computing
- Swarm intelligence
Track 3: Mining and Data Analysis
- Data Access
- Data Mining Foundations
- Parallel and Distributed Data mining Algorithms
- Data Streams Mining, Graph Mining
- Spatial Data mining, Text Video
- Multimedia Data Mining
- Web Mining
- Pre-processing Techniques
- Visualization
- Security and Information Hiding in Data Mining
- Data Mining Applications
- Databases
- Bioinformatics
- Biometrics
- Financial Modeling
- Forecasting
- Classification and Clustering
- Social Networks
- Educational Data Mining
- Knowledge Processing
- Data and Knowledge Representation
- Knowledge Discovery Framework and Process
- Integration of Data Warehousing
- Integrating Constraints and Knowledge in the KDD Process
- Exploring Data Analysis
- Explaining Discovered Knowledge
- Statistical Techniques for Generating a Robust
- Consistent Data Model
- Interactive Data Exploration/Visualization and Discovery
- Languages and Interfaces for Data Mining
- Mining Trends
Track 4: Robotics and Automation
- Agricultural Robotics
- Applications of Autonomous Intelligent Robots
- Autonomous Robotic Systems
- Computer Vision and Image Processing
- Control Architectures and Programming
- Cooperative Perception
- Cooperative Planning and Task Allocation
- Dexterous Manipulation and Grasping
- Educational Robotics
- Entertainment Robots
- Evolutionary Robotics
- Humanoid Robotics
- Human-Robot Interaction
- Intelligent Control systems
- Localization, Mapping, and Navigation
- Locomotion and Actuation Systems
- Multi-Robot Coordination
- Multi-Robot Systems
- Planning, Reasoning and Modelling
- Recognition and Tracking
- Robot Learning
- Robotic Competitions
- Robotic Simulation and control
- Sensors and Sensor Integration
- Swarm Robotics
- Space Robotics
- Underwater Robotics
Track 5: Image Processing and Computer Vision
- Activity Detection/ Recognition
- Biometrics, Forensics, Content Protection
- Computational Imaging
- Compressed Image/ Video Analytics
- Document Image Analysis
- Document and Synthetic Visual Processing
- Human Computer Interaction
- Image/ Video Scene Understanding
- Image/ Video Retrieval
- Image Enhancement /Super Resolution / Restoration
- Image/ Video Processing for Autonomous Vehicles
- Image/ Video Security
- Medical Image Analysis
- Motion and Tracking
- Remote Sensing, Hyperspectral Image Processing
- Segmentation and Shape Representation
- Visual Sensor Hardware
- Vision based Human GAIT Analysis
PUBLICATIONS
All accepted papers will be published in the conference proceeding which will be published by Springer in the series of “Advances in Intelligent Systems and Computing” and abstracted/indexed in DBLP, Google Scholar, EI-Compendex, Mathematical Reviews, SCImago, Scopus.
Student Best Paper Award
Papers accepted and presented in the conference and their first author is MSc or PhD students will be given the opportunity to compete for the Best Paper Award. The entries of the competition should be presented at the conference by the student.