L
Li Wang
Researcher at Chinese Academy of Sciences
Publications - 2891
Citations - 41475
Li Wang is an academic researcher from Chinese Academy of Sciences. The author has contributed to research in topics: Medicine & Biology. The author has an hindex of 71, co-authored 1622 publications receiving 26735 citations. Previous affiliations of Li Wang include Capital Medical University & Zhejiang University.
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Recent Advances in Convolutional Neural Networks
Jiuxiang Gu,Zhenhua Wang,Jason Kuen,Lianyang Ma,Amir Shahroudy,Bing Shuai,Ting Liu,Xingxing Wang,Li Wang,Gang Wang,Jianfei Cai,Tsuhan Chen +11 more
TL;DR: This paper details the improvements of CNN on different aspects, including layer design, activation function, loss function, regularization, optimization and fast computation, and introduces various applications of convolutional neural networks in computer vision, speech and natural language processing.
Journal ArticleDOI
Deep convolutional neural networks for multi-modality isointense infant brain image segmentation.
Wenlu Zhang,Rongjian Li,Houtao Deng,Li Wang,Weili Lin,Shuiwang Ji,Dinggang Shen,Dinggang Shen +7 more
TL;DR: This paper proposes to use deep convolutional neural networks (CNNs) for segmenting isointense stage brain tissues using multi-modality MR images, and compared the performance of the approach with that of the commonly used segmentation methods on a set of manually segmented isointENSE stage brain images.
Journal ArticleDOI
Active contours driven by local Gaussian distribution fitting energy
TL;DR: A new region-based active contour model in a variational level set formulation for image segmentation that is able to distinguish regions with similar intensity means but different variances and is demonstrated by applying the method on noisy and texture images.
Journal ArticleDOI
A review of lithium-ion battery safety concerns: The issues, strategies, and testing standards
Yuqing Chen,Yuqing Chen,Yuqiong Kang,Yun Zhao,Li Wang,Jilei Liu,Yanxi Li,Zheng Liang,Xiangming He,Xing Li,Naser Tavajohi,Baohua Li +11 more
TL;DR: In this paper, a review summarizes aspects of battery safety and discusses the related issues, strategies, and testing standards, concluding with insights into potential future developments and the prospects for safer lithium-ion batteries.
Book ChapterDOI
Deep learning based imaging data completion for improved brain disease diagnosis.
TL;DR: This work proposed a deep learning based framework for estimating multi-modality imaging data in the form of convolutional neural networks, where the input and output are two volumetric modalities.