Guang-Tong Zhou

904 citations
16 papers · 538 indexed · h-index 8
Topics
Advanced Image and Video Retrieval Techniques (4 papers)Image Retrieval and Classification Techniques (4 papers)Video Analysis and Summarization (3 papers)
Partner nations
ChinaCanadaAustralia

In The Last Decade

Guang-Tong Zhou

13 papers receiving 513 citations

Peers

Guang-Tong Zhou
Comparison fields: 5 of 114
  • Artificial Intelligence 320
  • Computer Vision and Pattern Recognition 173
  • Signal Processing 62
  • Electrical and Electronic Engineering 62
  • Computer Networks and Communications 47
Replace Ramón A. Mollineda with:
Ramón A. Mollineda Spain
Mario Manzo Italy
Cristiano Leite de Castro Brazil
Eric W. Cooper Japan
Katsuari Kamei Japan
I C G Campbell
Pablo Bermejo Spain
David A. Cieslak United States
Aida Ali Malaysia
Negin Samadi Iran
Guang-Tong Zhou relative to Ramón A. Mollineda Spain Ramón A. Mollineda's profile →
Citations per field
00.5×1.5×2.1×
Ramón A. Mollineda · 1×
Citations per year

Countries citing papers authored by Guang-Tong Zhou

Since Specialization
Citations

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

Fields of papers citing papers by Guang-Tong Zhou

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Guang-Tong Zhou. 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 Guang-Tong Zhou. The network helps show where Guang-Tong Zhou may publish in the future.

Co-authorship network of co-authors of Guang-Tong Zhou

This figure shows the co-authorship network connecting the top 25 collaborators of Guang-Tong Zhou. A scholar is included among the top collaborators of Guang-Tong Zhou 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 Guang-Tong Zhou. Guang-Tong Zhou is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

16 of 16 papers shown
#WorkIndexed citations
1 1
2 0
3 2
4 7
5 80
6 0
7 11
8
Latent Maximum Margin Clustering
15
9 6
10 29
11 16
12 38
13 18
14 2
15 311
16 2

About Guang-Tong Zhou

Guang-Tong Zhou is a scholar working on Computer Vision and Pattern Recognition, Statistics and Probability and Artificial Intelligence, having authored 16 papers that have together received 538 indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (4 papers), Image Retrieval and Classification Techniques (4 papers) and Video Analysis and Summarization (3 papers). The work is most often cited by research in Artificial Intelligence (320 citations), Computer Vision and Pattern Recognition (173 citations) and Signal Processing (62 citations). Guang-Tong Zhou has collaborated with scholars based in China, Canada and Australia. Frequent co-authors include Gongping Yang, Xinjian Guo, Cailing Dong, Yilong Yin, Greg Mori, Fei Tony Liu, Kai Ming Ting, Zhiwei Deng, Hexiang Hu and Zicheng Liao. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Pattern Recognition and Machine Learning.

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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