Chao Deng

947 citations
43 papers · 626 · h-index 13

Impact in

Papers in

Chao Deng

31 papers receiving 584 citations

Peers

Chao Deng
Comparison fields: 5 of 102
  • Acoustics and Ultrasonics 57
  • Instrumentation 31
  • Computer Vision and Pattern Recognition 164
  • Media Technology 64
  • Biophysics 35
Replace Takuya Funatomi with:
Takuya Funatomi Japan
Chang Chen China
Johannes Hanika Germany
Jin Li China
Jason Lawrence United States
Sanjay B. Dhok India
Sanjeev J. Koppal United States
Chris Wyman United States
Fan Shi China
Chao Deng relative to Takuya Funatomi Japan Takuya Funatomi's profile →
Citations per field
00.5×
Takuya Funatomi · 1×
Citations per year

Countries citing papers authored by Chao Deng

Since Specialization
Citations

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

Fields of papers citing papers by Chao Deng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 43 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2004105
2 2022103
3 200587
4 201756
5 201756
6 202238
7 202224
8 202123
9 201918
10 201417
11 202315
12 202313
13 202212
14 20159
15 20227
16 20136
17 20246
18 20245
19 20155
20 20144

About Chao Deng

Chao Deng is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Electrical and Electronic Engineering, Hardware and Architecture and Information Systems, having authored 43 papers that have together received 626 indexed citations. Recurring topics across this work include Topic Modeling (7 papers), Natural Language Processing Techniques (6 papers), Low-power high-performance VLSI design (5 papers), VLSI and FPGA Design Techniques (5 papers), Parallel Computing and Optimization Techniques (5 papers), Speech and dialogue systems (4 papers), Domain Adaptation and Few-Shot Learning (3 papers) and Neural Networks and Applications (3 papers). The work is most often cited by research in Acoustics and Ultrasonics (57 citations), Instrumentation (31 citations), Computer Vision and Pattern Recognition (164 citations), Media Technology (64 citations) and Biophysics (35 citations). Chao Deng has collaborated with scholars based in China, Singapore and United States. Frequent co-authors include Meng Joo Er, M.J. Er, Qionghai Dai, Jinli Suo, Qiulin Li, Ping Wu, Ben Xu, Jingtao Fan, Zhi Lü and Jiamin Wu. Their work appears in journals such as Frontiers in Psychology, IEEE Transactions on Pattern Analysis and Machine Intelligence, Applied Sciences, Neurocomputing and IEEE Transactions on Mobile Computing.

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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