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Yang Yang
Researcher at University of Electronic Science and Technology of China
Publications - 563
Citations - 19966
Yang Yang is an academic researcher from University of Electronic Science and Technology of China. The author has contributed to research in topics: Computer science & Medicine. The author has an hindex of 51, co-authored 419 publications receiving 13362 citations. Previous affiliations of Yang Yang include Nanyang Technological University & National University of Singapore.
Papers
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Journal ArticleDOI
NEDD4L-induced β-catenin ubiquitination suppresses the formation and progression of interstitial pulmonary fibrosis via inhibiting the CTHRC1/HIF-1α axis.
TL;DR: In this paper, the downregulated level of neural precursor cell expressed developmentally downregulated 4-like protein (NEDD4L) in IPF-related expression microarray dataset, and this study was thus performed to explore the molecular mechanism of NEDD-4L in lung disease.
Proceedings ArticleDOI
GPU accelerated high-dimensional compressed sensing MRI
TL;DR: The preliminary study indicates that the proposed CS method offers further acceleration in acquisition and also improves image quality, and a parallelized implementation of the HOSVD-based CS reconstructions using a graphics processing unit (GPU) is presented.
Journal ArticleDOI
Generating and Detecting Broad-Band Underwater Multiple OAMs Based on Water-Immersed Array
Yang Yang,Liu Gao,Fei Shen,Jianhua Sun,Kai Guo,Zhongyi Guo,Qing Zhou,Haibo Jiang,Zhe Wu,Baoqing Zeng,Yubin Gong +10 more
TL;DR: Experimental results validate that the proposed underwater antenna array can readily generate high-quality vortex waves and compare the performances of two generation methods to know that the first generation method with a smaller structure costs lower and is more efficient.
Journal ArticleDOI
Size Constrained Clustering With MILP Formulation
TL;DR: Experiments on UCI data sets indicate that imposing the size constraints as proposed could improve the clustering performance; and compared with the state-of-the-art size constrained clustering methods, the proposed method could efficiently derive better clustering results.
Journal ArticleDOI
Sparse Graph Connectivity for Image Segmentation
TL;DR: Wang et al. as discussed by the authors proposed a sparse graph connectivity (SGC) method for image segmentation to automatically learn the affinity matrix from the low-dimensional space of original data, which aims at simultaneously achieving subspace preservation and graph connectivity.