De Cheng

1.8k citations
24 papers · 1.3k indexed · 1 hit paper · h-index 12

De Cheng

24 papers receiving 1.3k citations

Hit Papers

Person Re-identification by Multi-Channel Parts-Based CNN...8902016202620192022250500750

Peers

De Cheng
Comparison fields: 5 of 92
  • Computer Vision and Pattern Recognition 1.1k
  • Biomedical Engineering 454
  • Artificial Intelligence 200
  • Media Technology 50
  • Safety, Risk, Reliability and Quality 51
Replace Yang Wu with:
Yang Wu China
Hehe Fan China
Zhilan Hu China
Peixi Peng China
Shuyang Sun United Kingdom
Haiyu Zhao Singapore
Hong-Xing Yu China
De Cheng relative to Yang Wu China Yang Wu's profile →
Citations per field
00.5×8.4×
Yang Wu · 1×
Citations per year

Countries citing papers authored by De Cheng

Since Specialization
Citations

This map shows the geographic impact of De Cheng'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 De Cheng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites De Cheng more than expected).

Fields of papers citing papers by De Cheng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by De Cheng. 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 De Cheng. The network helps show where De Cheng may publish in the future.

Co-authorship network

The 25 scholars most cited alongside De Cheng, 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 De Cheng Line = papers co-authored together De Cheng links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20252
2 201917
3 201815
4 201846
5 201822
6 20188
7 201844
8 20189
9 201860
10 201756
11 201741
12 20171
13 201711
14 201713
15 201713
16 201721
17 20164
18
Person Re-identification by Multi-Channel Parts-Based CNN with Improved Triplet Loss Functionbreakdown →
2016890
19 200911
20 20083

About De Cheng

De Cheng is a scholar working on Computer Vision and Pattern Recognition, Hepatology, Artificial Intelligence, Human-Computer Interaction and Geology, having authored 24 papers that have together received 1.3k indexed citations. Recurring topics across this work include Video Surveillance and Tracking Methods (11 papers), Human Pose and Action Recognition (7 papers), Advanced Image and Video Retrieval Techniques (6 papers), Face recognition and analysis (5 papers), Advanced Neural Network Applications (5 papers), Gait Recognition and Analysis (4 papers), Hepatitis C virus research (3 papers) and Liver Disease Diagnosis and Treatment (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.1k citations), Biomedical Engineering (454 citations), Artificial Intelligence (200 citations), Media Technology (50 citations) and Safety, Risk, Reliability and Quality (51 citations). De Cheng has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Yihong Gong, Nanning Zheng, Jinjun Wang, Sanping Zhou, Weiwei Shi, Huaxiang Zhang, Xiaoyu Tao, Xiaojun Chang, Yi Yang and Zhihui Li. Their work appears in journals such as Neurocomputing, Pattern Recognition, Multimedia Tools and Applications, Pattern Recognition Letters and European Journal of Clinical Microbiology & Infectious Diseases.

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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