Guest Editors
Dr. Yu Zhou, Shenzhen University, China
Dr. Eneko Osaba, TECNALIA Research & Innovation, Spain
Dr. Xiao Zhang, South-Central Minzu University, China
Summary
Artificial intelligence techniques, such as Deep learning (DL) methods, have demonstrated their great success in the past ten years for various applications, such as computer vision, bioinformatics, healthcare and transportation. As the field of deep learning evolves rapidly, new and innovative approaches continue to emerge, addressing complex challenges in real-world applications. When facing emerging real-world applications, current DL models still suffer from high-dimensionality issue, robustness, data uncertainty and lack of global convergence and interpretability. Recent developments in intelligent computing approaches suggest the potential for next-generation deep learning methodologies that effectively address these challenges, such as bio-inspired computing, brain-inspired computing and other new computing schemes. This special issue aims to bring together cutting-edge research that showcases the next-generation deep learning approaches and their applications in emerging real-world scenarios, which aims to explore:
1) Novel deep learning models and structures.
2) New optimization method for deep learning training
3) Emerging real-world applications
The topics include those related to novel deep learning approaches and emerging real-world applications, but not limited to, the following:
Bio-inspired computing methods with deep leaning
Brain-inspired computing methods with deep learning
Attention mechanism in deep learning
Sparse deep learning
Soft computing with deep learning
Ensemble deep learning
Fine-tune methods for deep learning
Graph deep learning
Emerging topics in healthcare and sports with deep learning
Emerging topics in smart city and transportation with deep learning
Emerging topics in industrial informatics and intelligent manufacturing with deep learning
Emerging topics in social sciences with deep learning
Keywords
Deep learning, emerging real-world applications, intelligent computing
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