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Guangming Shi
Researcher at Xidian University
Publications - 488
Citations - 14046
Guangming Shi is an academic researcher from Xidian University. The author has contributed to research in topics: Computer science & Sparse approximation. The author has an hindex of 41, co-authored 428 publications receiving 10591 citations. Previous affiliations of Guangming Shi include Chinese Ministry of Education.
Papers
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Journal ArticleDOI
Improving Robotic Tactile Localization Super-resolution via Spatiotemporal Continuity Learning and Overlapping Air Chambers
TL;DR: In this article , the authors proposed a method for robotic tactile super-resolution enhancement by learning spatio-temporal continuity of contact position and a tactile sensor composed of overlapping air chambers, where each overlapping air chamber is constructed of soft material and sealed the barometer inside to mimic adapting receptors of human skin.
Journal ArticleDOI
Supervised Contrastive Learning Based on Fusion of Global and Local Features for Remote Sensing Image Retrieval
TL;DR: Wang et al. as mentioned in this paper proposed a supervised contrastive learning based on the fusion of global and local features method, named SCFR, to enhance the ability of image expression.
Proceedings ArticleDOI
Perceptual spatial-temporal video compressive sensing network
TL;DR: The proposed spatial-temporal VCS network can achieve better visual effect with less recovery time than the state-of-the-art, and the refined perceptual loss can guide the spatial- Temporal network to retain more textures and structures.
Proceedings ArticleDOI
ISAR imaging with separable sparse representation model
TL;DR: A novel separable SR-based ISAR imaging algorithm is developed by introducing a separable observation model, where the large-scale basis is replaced by two small-scale bases, which brings significant reduction on memory and complexity.
Book ChapterDOI
A new fast algorithm for training large window stack filters
TL;DR: A new fast adaptive algorithm for designing a stack filter with large windows to divide a lager window into many sub-windows and it is shown that the algorithm is effective and feasible.