Tao Deng

763 citations
57 papers · 500 indexed · h-index 11
Topics
Advanced Neural Network Applications (14 papers)Video Surveillance and Tracking Methods (12 papers)Autonomous Vehicle Technology and Safety (10 papers)
Partner nations
ChinaUnited StatesCanada

In The Last Decade

Tao Deng

48 papers receiving 485 citations

Peers

Tao Deng
Comparison fields: 5 of 70
  • Computer Vision and Pattern Recognition 249
  • Automotive Engineering 100
  • Electrical and Electronic Engineering 83
  • Human-Computer Interaction 71
  • Computer Networks and Communications 55
Replace Yuki Uranishi with:
Yuki Uranishi Japan
Jenn-Jier James Lien Taiwan
Kunyu Peng Germany
Pedro Núñez Spain
Alberto Fernández Spain
Zhiwen Shao China
Bhakti Baheti India
Naohisa Hashimoto Japan
Stephen Wood United States
Cătălin Daniel Căleanu Romania
Tao Deng relative to Yuki Uranishi Japan Yuki Uranishi's profile →
Citations per field
00.5×
Yuki Uranishi · 1×
Citations per year

Countries citing papers authored by Tao Deng

Since Specialization
Citations

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

Fields of papers citing papers by Tao Deng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tao Deng

This figure shows the co-authorship network connecting the top 25 collaborators of Tao Deng. A scholar is included among the top collaborators of Tao Deng based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Tao Deng. Tao Deng is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 0
3 1
4 1
5 3
6 0
7 2
8 0
9 1
10 0
11 3
12 1
13 5
14 3
15 16
16 45
17 68
18 3
19 11
20
RECOVERING THE MISSING DATA OF DEFECTIVE FOSSIL SPECIMENS USING LINEAR REGRESSION METHOD
2

About Tao Deng

Tao Deng is a scholar working on Computer Vision and Pattern Recognition, Automotive Engineering and Human-Computer Interaction, having authored 57 papers that have together received 500 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (14 papers), Video Surveillance and Tracking Methods (12 papers) and Autonomous Vehicle Technology and Safety (10 papers). The work is most often cited by research in Human-Computer Interaction (71 citations), Computer Vision and Pattern Recognition (249 citations) and Automotive Engineering (100 citations). Tao Deng has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Hongmei Yan, Yongjie Li, Long Qin, Fei Yan, Kai-Fu Yang, B.S. Manjunath, Jiyong Zhang, Ravikumar Pragada, B. Raghothaman and Xian-Shi Zhang. Their work appears in journals such as Scientific Reports, Expert Systems with Applications and Energy.

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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