Self-supervised learning for time-series data has broad application potential in smartphone-based early disease detection. However, time-series data often exhibit complex dynamic patterns and spatiotemporal correlations. These characteristics make it difficult to capture discriminative features and reconstruct local fe...
Tongyue He, Qiang He, Jun Mou et al.· IEEE Transactions on Instrum...· 0 citations
This survey systematically categorizes the 30‐year evolution of image inpainting into three distinct technological generations: traditional prior‐driven synthesis, deep learning data‐driven reconstruction and modern foundation model‐driven generation, providing a definitive reference for future theoretical and engineer...
Zhenhua Yu, Heng-Xiang Zhao, Wen-Chao Zhang et al.· Expert Syst. J. Knowl. Eng.· 0 citations
This survey deeply explains the basic principles of representation learning, and introduces its practical application cases in various fields, and points out the main limitations of current models and prospects the future research directions.
Zhiyong Wang, Qiang He, Jun Mou et al.· Expert systems· 0 citations
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