Narrative Review
Narrative reviews synthesize existing research to provide a comprehensive overview of a specific topic, aiming to identify key trends, gaps, and future research directions. Current research focuses on applying narrative reviews across diverse fields, employing various model architectures like graph neural networks, large language models, and diffusion models to analyze complex data and improve model interpretability and efficiency. This approach is crucial for advancing scientific understanding and informing the development of practical applications in areas such as medicine, engineering, and manufacturing.
Papers
Deep Learning Techniques for Hyperspectral Image Analysis in Agriculture: A Review
Mohamed Fadhlallah Guerri, Cosimo Distante, Paolo Spagnolo, Fares Bougourzi, Abdelmalik Taleb-Ahmed
Tensor Decomposition for Model Reduction in Neural Networks: A Review
Xingyi Liu, Keshab K. Parhi
Games for Artificial Intelligence Research: A Review and Perspectives
Chengpeng Hu, Yunlong Zhao, Ziqi Wang, Haocheng Du, Jialin Liu