IJGAIC Journal

Aim

The primary aim of IJGAIC is to:

Promote cutting-edge research in generative AI and intelligent computing technologies.

Encourage interdisciplinary innovation combining AI, machine learning, computational intelligence, and advanced computing paradigms.

Provide a global forum for discussion of emerging theories, models, tools, and applications.

Support responsible AI practices, including transparency, fairness, security, and governance.

Accelerate knowledge transfer between research communities and industry practitioners.

Scope

The journal welcomes high-quality contributions in, but not limited to, the following areas:

Generative Artificial Intelligence
- Large Language Models (LLMs)
- AI Content Generation
- Generative Adversarial Networks (GANs)
- AI-based Text, Image, Audio, and Video Generation
- Prompt Engineering
- AI Agents and Autonomous Systems
Machine Learning and Deep Learning
- Supervised and Unsupervised Learning
- Predictive Analytics
- Deep Neural Networks
- Transfer Learning
- Ensemble Learning
- Intelligent Recommendation Systems
Natural Language Processing (NLP)
- Text Mining and Sentiment Analysis
- Chatbots and Conversational AI
- Language Translation Systems
- Speech Recognition
- Information Retrieval
- Named Entity Recognition
Computer Vision and Image Processing
- Object Detection and Recognition
- Facial Recognition Systems
- Medical Image Analysis
- Pattern Recognition
- Video Analytics
- Augmented Reality and Visual Intelligence
Intelligent Computing Systems
- Intelligent Decision Support Systems
- Smart Computing Architectures
- Adaptive Computing Models
- Intelligent Automation
- Context-Aware Systems
- Smart Monitoring and Control Systems
Neural Networks and Cognitive Computing
- Artificial Neural Networks (ANN)
- Convolutional Neural Networks (CNN)
- Recurrent Neural Networks (RNN)
- Cognitive Learning Models
- Brain-Inspired Computing
- Self-Learning Intelligent Systems

IJGAIC – Peer-Reviewed Journal