Full Paper Submission 30 June 2022
GCAIA 2022 is a three-day International Conference specially designed with a cluster of scientific and technological sessions, providing a common platform for researchers, academicians, industry delegates, scientists, professionals, industry and government policy-makers, engineers, and students across the globe to share and exchange their knowledge and contribution. This conference attends to emerging areas of research and development related to the new challenges presented by the COVID-19 pandemic, focusing specifically upon aspects and applications of artificial intelligence.
The conference is equipped with well-organized scientific sessions, keynote and plenary lectures, research papers, poster presentations, and world-class exhibitions.
This conference also has some special sessions related to innovative applications with Artificial Intelligence, Internet of Things, and Cloud Computing and a demo session for innovations achieved through prototyping and simulation.
Topics and technical areas of interest include but are not limited to the following:
Artificial Intelligence
- Learning Techniques
- Neural Networks
- Soft Computing
- Expert Systems
- Computational Intelligence
- Natural Language Processing
- Data Mining
- Neuromorphic systems
- Biometrics
- Sentiment Analysis
Machine Vision
- Human-Computer Interaction
- Pattern Recognition
- Image/Video Processing
- Intrusion Detection
- Geographic Information Systems
- Brain-Machine Interface
- Signal Processing
- Medical Diagnosis
- Segmentation Techniques
- Augmented/Virtual Reality
Robotics
- Humanoid Robots
- Space and underwater robots
- Assistive Robots
- Mobile Robots
- Autonomous Robots
- Human-Robot Interaction
- Telerobotics
- Walking and Climbing Robots
- Robotic Automation
- Robot Localization and Map Building
Ambient Intelligence
- Smart Cities
- Internet of Things
- Ambient Assisted Living
- Smart Healthcare
- Intelligent Transportation
- Data Science
- Particle Swarm Optimization
- Neural Network Theory & Architecture
- Collective Intelligence
- Rough Set and Rough Data Analysis