Guest Editors
Prof. Dae-Ki Kang
Email: dkkang@dongseo.ac.kr
Affiliation: Department of Computer Engineering, Dongseo University, Busan, 47011, South Korea
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Research Interests: Adversarial Machine Learning, Generative Models, Deep Reinforcement Learning, Hyperparameter Optimization and Network Architecture Search, Multi-Agent Reinforcement Learning, Bankruptcy prediction models and financial ratio analysis, Datamining based intrusion detection
Summary
Deep learning and neural networks have revolutionized various fields, including computer vision, natural language processing, and healthcare. As these technologies continue to evolve, it is essential to explore their latest advancements, applications, and challenges. This special issue aims to gather innovative research contributions that highlight significant progress and practical implementations of deep learning and neural networks.
We invite original research articles and reviews that cover, but are not limited to, the following topics:
1. Architectural Innovations:
- Novel neural network architectures (e.g., CNNs, RNNs, GANs, Transformers)
- Techniques for improving model efficiency and performance
2. Training and Optimization:
- Advanced training methods (e.g., transfer learning, reinforcement learning)
- Optimization algorithms and their impact on convergence
3. Applications:
- Use cases in various domains, including:
- Healthcare: medical imaging, diagnosis, and treatment planning
- Autonomous systems: robotics and self-driving cars
- Finance: fraud detection and algorithmic trading
- Environmental science: climate modeling and resource management
4. Ethics and Fairness:
- Addressing bias and fairness in deep learning models
- Ethical considerations in AI deployment
5. Future Directions:
- Large Language Models
- Emerging trends and future challenges in deep learning research
- Interdisciplinary approaches combining deep learning with other fields
Keywords
Deep Learning, Neural Networks, Transformers, Large Language Models
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