The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Ruiping Wang sits on this spectrum.
This scientist: 115 publications — 13th percentile
13% of scientists in this discipline score the same or lower.
The last bar groups every scientist with 991 publications or more.
The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Ruiping Wang sits on this spectrum.
This scientist: 37 D-Index — 27th percentile
27% of scientists in this discipline score the same or lower.
The last bar groups every scientist with 131 D-Index or more.
Ruiping Wang is a researcher affiliated with the Chinese Academy of Sciences in China, with a primary focus on computer science and related subfields. Their body of work includes significant contributions to computer vision, pattern recognition, and artificial intelligence. The scientist's research spans various domains, including advanced neural network applications and domain adaptation, emphasizing multimodal machine learning applications and advanced image and video retrieval techniques.
They have published more than 100 papers, with 66 in computer vision and pattern recognition and 34 related to artificial intelligence. Additional subfields include computational mechanics, polymers and plastics, and media technology. Major topics covered in their research include:
Ruiping Wang has collaborated frequently with a number of co-authors, reflecting a broad network within the field. These co-authors include Xilin Chen, Shiguang Shan, Miaojun Xu, Xian Sun, and Peijin Wang.
The scientist's recent publication record features works in notable venues, predominantly:
Selected recent publications exemplify the scope of their research interests and outputs:
The topics addressed in these publications indicate active engagement with remote sensing, few-shot learning, and continual learning challenges in computer vision. The synthesis of domain adaptation methodologies with advanced machine learning techniques appears central to their contributions.
Haomiao Liu;Ruiping Wang;Shiguang Shan;Xilin Chen
Ruiping Wang;Shiguang Shan;Xilin Chen;Wen Gao
Ruiping Wang;Huimin Guo;Larry S. Davis;Qionghai Dai
Mengyi Liu;Shiguang Shan;Ruiping Wang;Xilin Chen
Ruiping Wang;Xilin Chen
Mengyi Liu;Shaoxin Li;Shiguang Shan;Ruiping Wang
Wen Wang;Ruiping Wang;Zhiwu Huang;Shiguang Shan
Unknown
Zhiwu Huang;Ruiping Wang;Shiguang Shan;Xilin Chen
Yong Liu;Ruiping Wang;Shiguang Shan;Xilin Chen
Zhiwu Huang;Ruiping Wang;Shiguang Shan;Xianqiu Li
Sijin Wang;Ruiping Wang;Ziwei Yao;Shiguang Shan
Mengyi Liu;Ruiping Wang;Shaoxin Li;Shiguang Shan
Huajie Jiang;Ruiping Wang;Shiguang Shan;Xilin Chen
Zhiwu Huang;Shiguang Shan;Ruiping Wang;Haihong Zhang
Ruiping Wang;Shiguang Shan;Xilin Chen;Qionghai Dai
Huajie Jiang;Ruiping Wang;Shiguang Shan;Xilin Chen
Huajie Jiang;Ruiping Wang;Shiguang Shan;Yi Yang
Difei Gao;Ke Li;Ruiping Wang;Shiguang Shan
Zhiwu Huang;Ruiping Wang;Shiguang Shan;Xilin Chen
Zhiwu Huang;Ruiping Wang;Shiguang Shan;Xilin Chen
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