Results 71 to 80 of about 3,935,477 (223)

UDSFS: Unsupervised deep sparse feature selection

, 2016
In this paper, we focus on unsupervised feature selection. As we have known, the combination of several feature units into a whole feature vector is broadly adopted for effective object representation, which may inevitably includes some irrelevant ...
Fan BJ(范保杰), Yu HB(于海斌), Yang YS(杨云生), Cong Y(丛杨), Wang S(王帅)   +4 more
core  

Ferroelectric Devices for In‐Memory and In‐Sensor Computing

Advanced Science, EarlyView.
Inspired by biological systems, in‐memory and in‐sensor computing overcome von Neumann bottlenecks. Ferroelectric devices can mimic synaptic functions and sense stimuli like light or force, therefore are ideal for these paradigms. This review introduces the ferroelectric devices applied for in‐memory and in‐sensor computing, covering their structures ...
Hong Fang, Ronghuan Xie, Qiang Cao, Shishen Yan, Xiaolin Wang, Limei Zheng   +5 more
wiley   +1 more source

Unsupervised Band Selection using Block Diagonal Sparsity for Hyperspectral Image Classification

, 2017
International audienceIn order to alleviate the negative effect of curse of dimensionality, band selection is a crucial step for hyperspectral image (HSI) processing.
Madani, K., K., Pei Wang, Sabourin, C., Madani, K.,, Zhang, K., Christophe Sabourin, Ke Zhang, Wang, J., Kurosh Madani, Pei, P., Jingyu Wang   +10 more
core   +1 more source

Single‐Cell Dissection of Microglial Dysfunction in Diabetes‐Associated Neurodegenerative Vulnerability

Advanced Science, EarlyView.
Using single‐cell transcriptomic and epigenomic profiling, researchers mapped microglial dysfunction across the lifespan of db/db mice. The authors uncovered a nonlinear microglial remodeling featuring early inflammatory priming, a mid‐stage transcriptional inflection, and late dysfunction.
Jizhou Zhang, Tsz Kwan Yau, Joyce Tse, Tsz Ho Li, Dongjie Hu, Yong Juan Zhao, Ting‐Fung Chan   +6 more
wiley   +1 more source

Wrapped Unsupervised Hyperspectral Band Selection via Reconstruction Error from Wasserstein Generative Adversarial Network

Remote Sensing
Wrapped unsupervised band selection (WUBS) is a powerful means of reducing the dimensions of hyperspectral images (HSIs) and has drawn much focus recently.
Haoyang Yu, Hongna Zheng, Tao Yao, Yuling Zhang, Deyin Zhang   +4 more
doaj   +1 more source

Unsupervised Hyperspectral Band Selection Based on Maximum Information Entropy and Determinantal Point Process

, 2018
Band selection is of great important for hyperspectral image processing, which can effectively reduce the data redundancy and computation time. In the case of unknown class labels, it is very difficult to select an effective band subset.
Cai, Nian, Zhijing Yang, Yijun Yan, Cao, Faxian, Yang, Zhijing, Faxian Cao, Chen, Weizhao, Weizhao Chen, Nian Cai, Yan, Yijun   +9 more
core   +1 more source

Photonic‐Enabled Energy‐Efficient Transparent Neuromorphic Computing Devices: A Review

Advanced Science, EarlyView.
Transparent photonic neuromorphic computing devices merge optics and brain‐inspired computing to overcome von Neumann bottlenecks with ultrafast, low‐energy processing. By exploiting transparent oxides, 2D materials, phase‐change materials, and hybrid heterostructures, these platforms enable photonic synapses, memory, and logic for see‐through edge ...
Shuvaraj Ghosh, Ki‐bum Lee, Junghyeon Lee, Seunghee Cho, Malkeshkumar Patel, Hangfei Li, Yu Wen, Ye Zhou, Joondong Kim   +8 more
wiley   +1 more source

Band Priority Index: A Feature Selection Framework for Hyperspectral Imagery

Remote Sensing, 2018
Hyperspectral Band Selection (BS) aims to select a few informative and distinctive bands to represent the whole image cube. In this paper, an unsupervised BS framework named the band priority index (BPI) is proposed.
Wenqiang Zhang, Xiaorun Li, Liaoying Zhao   +2 more
doaj   +1 more source

Tissue‐Agnostic Cellular Morphometric Biomarkers for Risk‐Adapted Management Across Gastrointestinal Precancerous Lesions and Cancers

Advanced Science, EarlyView.
An interpretable, unsupervised artificial intelligence framework identifies a 13‐cellular morphometric biomarker (CMB) signature from routine H&E whole‐slide images. Validated across 2,602 patients, the fixed signature generalizes across colorectal, gastric, and esophageal tissues without retraining, stratifies prognosis and precancerous lesion risk ...
Pin Wang, Chengfei Jiang, April W. Mao, Qi Sun, Yijun Lu, Jingjing Wei, Jamie L. Inman, Susan E. Celniker, Antoine M. Snijders, David W. Threadgill, Allan Balmain, Bo Hang, Hang Chang, Lei Wang, Jian‐Hua Mao   +14 more
wiley   +1 more source

SerpinA3 is an Endogenous TGF‐β Receptor Antagonist that Attenuates Cardiac Fibroblast Activation and Fibrotic Remodeling

Advanced Science, EarlyView.
SerpinA3 acts as an endogenous TGF‐β receptor antagonist that binds to the extracellular domain of TGFR‐1, thereby preventing TGFR‐1–TGFR‐2 complex formation. This receptor‐level blockade suppresses TGF‐β/Smad2/3 signaling, attenuates cardiac fibroblast activation, and extracellular matrix deposition, and ultimately alleviates pressure overload–induced
Hui Wang, Jieyu Cui, Chunlu Huang, Wanyi Guo, Tong Liu, Yi Zhu, Shuai Shao, Kangyin Chen, Jinlong He, Qiankun Bao   +9 more
wiley   +1 more source