Keshu Zhang

1.3k citations
43 papers · 1.0k indexed · 1 hit paper · h-index 15
Topics
Target Tracking and Data Fusion in Sensor Networks (13 papers)Distributed Sensor Networks and Detection Algorithms (9 papers)Fault Detection and Control Systems (8 papers)
Journals
SHILAP Revista de lepidopterologíaAutomaticaIEEE Transactions on Signal Processing
Partner nations
United StatesChinaJapan

In The Last Decade

Keshu Zhang

40 papers receiving 958 citations

Hit Papers

Rotation-aware and multi-scale convolutional neural netwo...2020202620222024202050100150200

Peers

Keshu Zhang
Comparison fields: 5 of 86
  • Artificial Intelligence 512
  • Computer Vision and Pattern Recognition 336
  • Computer Networks and Communications 313
  • Control and Systems Engineering 227
  • Aerospace Engineering 178
Replace Ignácio Bravo with:
Ignácio Bravo Spain
Mete Özay Türkiye
Angelo Coluccia Italy
Mahendra Mallick United States
Subhash Challa Australia
Pedro M. Q. Aguiar Portugal
Xin Du China
Faisal Z. Qureshi Canada
Chris Kreucher United States
Rongke Liu China
Keshu Zhang relative to Ignácio Bravo Spain Ignácio Bravo's profile →
Citations per field
00.5×4.5×
Ignácio Bravo · 1×
Citations per year

Countries citing papers authored by Keshu Zhang

Since Specialization
Citations

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

Fields of papers citing papers by Keshu Zhang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Keshu Zhang

This figure shows the co-authorship network connecting the top 25 collaborators of Keshu Zhang. A scholar is included among the top collaborators of Keshu Zhang 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 Keshu Zhang. Keshu Zhang 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 7
2 13
3 1
4 1
5 6
6 3
7 1
8 3
9 1
10 6
11 10
12 2
13 18
14 103
15 66
16
Efficient and Robust Feature Extraction by Maximum Margin Criterion
72
17 13
18 8
19 4
20 1

About Keshu Zhang

Keshu Zhang is a scholar working on Instrumentation, Artificial Intelligence and Transportation, having authored 43 papers that have together received 1.0k indexed citations. Recurring topics across this work include Target Tracking and Data Fusion in Sensor Networks (13 papers), Distributed Sensor Networks and Detection Algorithms (9 papers) and Fault Detection and Control Systems (8 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (336 citations), Media Technology (140 citations) and Artificial Intelligence (512 citations). Keshu Zhang has collaborated with scholars based in United States, China and Japan. Frequent co-authors include X.R. Li, Yunmin Zhu, Tao Jiang, Guangluan Xu, Yue Zhang, Kun Fu, Juan Zhao, Xian Sun, Zhonghan Chang and Zhisheng You. Their work appears in journals such as SHILAP Revista de lepidopterología, Automatica and IEEE Transactions on Signal 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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