Shaohua Teng

2.5k total citations
130 papers, 1.7k citations indexed

About

Shaohua Teng is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, Shaohua Teng has authored 130 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 54 papers in Computer Vision and Pattern Recognition, 52 papers in Artificial Intelligence and 36 papers in Computer Networks and Communications. Recurrent topics in Shaohua Teng's work include Network Security and Intrusion Detection (27 papers), Face and Expression Recognition (18 papers) and Domain Adaptation and Few-Shot Learning (15 papers). Shaohua Teng is often cited by papers focused on Network Security and Intrusion Detection (27 papers), Face and Expression Recognition (18 papers) and Domain Adaptation and Few-Shot Learning (15 papers). Shaohua Teng collaborates with scholars based in China, Macao and Canada. Shaohua Teng's co-authors include Lunke Fei, Xiaozhao Fang, Haibin Zhu, Wei Zhang, Dongning Liu, Luyao Teng, Naiqi Wu, Wei Zhang, Wei Jia and David Zhang and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing and Analytica Chimica Acta.

In The Last Decade

Shaohua Teng

115 papers receiving 1.7k citations

Peers

Shaohua Teng
Comparison fields: 5 of 118
  • Computer Vision and Pattern Recognition 795
  • Artificial Intelligence 551
  • Signal Processing 450
  • Computer Networks and Communications 278
  • Information Systems 179
Replace El-Sayed M. El-Alfy with:
El-Sayed M. El-Alfy Saudi Arabia
Pradeep K. Atrey United States
Sangyoun Lee South Korea
Marco Bertini Italy
Hong-Han Shuai Taiwan
Haoxiang Wang China
Sambit Bakshi India
Qi Wang United Kingdom
Shaojie Qiao China
Abdul Rehman Pakistan
El-Sayed M. El-Alfy Saudi Arabia View profile →
Citations per field, relative to Shaohua Teng
Shaohua Teng · 1×
Citations per year, relative to Shaohua Teng
Shaohua Teng · 1×

Countries citing papers authored by Shaohua Teng

Since Specialization
Citations

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

Fields of papers citing papers by Shaohua Teng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shaohua Teng

This figure shows the co-authorship network connecting the top 25 collaborators of Shaohua Teng. A scholar is included among the top collaborators of Shaohua Teng 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 Shaohua Teng. Shaohua Teng 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
# Work Indexed citations
1 1
2 1
3 2
4 6
5 1
6 0
7 1
8 5
9 9
10 5
11 7
12 3
13 10
14 13
15 59
16 8
17 13
18 19
19 37
20
Improved ACO-based wireless sensor networks routing
2

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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