Wei Wang

303 papers receiving 5.4k citations

Wei Wang's Hit Papers

Hierarchical recurrent neural network for skeleton based action recognition 2015 · 1.3k citations
1.3k0+3+7Years since publication4008001.2k

Peers

Wei Wang
Comparison fields: 5 of 192
  • Nuclear Energy and Engineering 46
  • Human-Computer Interaction 406
  • Computer Vision and Pattern Recognition 1.5k
  • Pollution 407
  • Civil and Structural Engineering 688
Replace Pan Pan with:
Pan Pan China
Chunwei Zhang China
Wang Li China
Xinmin Wang China
Xiaoling Wang China
Feng Zhao China
Han‐Seung Lee South Korea
Andreas Ludwig Austria
Jian Li China
Fei Liu China
Wei Wang relative to Pan Pan China Pan Pan's profile →
Citations per field
00.5×11.6×
Pan Pan · 1×
Citations per year

Countries citing papers authored by Wei Wang

Since Specialization
Citations

This map shows the geographic impact of Wei Wang's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Wei Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Wei Wang more than expected).

Fields of papers citing papers by Wei Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Wei Wang. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Wei Wang. The network helps show where Wei Wang may publish in the future.

Co-authors

The 25 scholars most cited alongside Wei Wang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Wei Wang Line = papers co-authored together Wei Wang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 358 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Hierarchical recurrent neural network for skeleton based action recognition
Hit paper breakdown →
20151262
2 2014261
3 2013154
4 2010153
5 2014129
6 201889
7 201884
8 200678
9 202067
10 202264
11 202262
12 201360
13 201456
14 202155
15 200655
16 201851
17 201451
18 202149
19 202247
20 202146

About Wei Wang

Wei Wang is a scholar working on Biomedical Engineering, Materials Chemistry, Civil and Structural Engineering, Electrical and Electronic Engineering and Pollution, having authored 358 papers that have together received 5.5k indexed citations. Recurring topics across this work include Perovskite Materials and Applications (17 papers), Conducting polymers and applications (16 papers), Concrete and Cement Materials Research (15 papers), Smart Materials for Construction (15 papers), Innovative concrete reinforcement materials (14 papers), Advanced Sensor and Energy Harvesting Materials (14 papers), Heavy metals in environment (13 papers) and Soil and Unsaturated Flow (12 papers). The work is most often cited by research in Nuclear Energy and Engineering (46 citations), Human-Computer Interaction (406 citations), Computer Vision and Pattern Recognition (1.5k citations), Pollution (407 citations) and Civil and Structural Engineering (688 citations). Wei Wang has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Liang Wang, Y. Du, Yan Huang, Yizhou Wang, Yushi Liu, Mingzhi Wang, Rui Xin Huang, Yu Zhang, Zhengguang Zhang and Yulin Yang. Their work appears in journals such as Chemical Engineering Journal, Construction and Building Materials, Advanced Functional Materials, Optics Express and IEEE Transactions on Image Processing.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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