Lekha Chaisorn

443 citations
32 papers · 274 indexed · h-index 8
Topics
Video Analysis and Summarization (21 papers)Advanced Image and Video Retrieval Techniques (19 papers)Image Retrieval and Classification Techniques (9 papers)
Partner nations
SingaporeChinaThailand

In The Last Decade

Lekha Chaisorn

30 papers receiving 248 citations

Peers

Lekha Chaisorn
Comparison fields: 5 of 27
  • Computer Vision and Pattern Recognition 245
  • Signal Processing 102
  • Artificial Intelligence 70
  • Sociology and Political Science 34
  • Information Systems 19
Replace Shi-Yong Neo with:
Shi-Yong Neo Singapore
Georg Thallinger Austria
Cuneyt M. Taskiran United States
A. Yoshitaka Japan
Tajuddin Manhar Mohammed United States
Akira Yanagawa United States
Philip Bontrager United States
G. Ahanger United States
Arding Hsu United States
Christos Tzelepis United Kingdom
Lekha Chaisorn relative to Shi-Yong Neo Singapore Shi-Yong Neo's profile →
Citations per field
00.5×3.6×
Shi-Yong Neo · 1×
Citations per year

Countries citing papers authored by Lekha Chaisorn

Since Specialization
Citations

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

Fields of papers citing papers by Lekha Chaisorn

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lekha Chaisorn

This figure shows the co-authorship network connecting the top 25 collaborators of Lekha Chaisorn. A scholar is included among the top collaborators of Lekha Chaisorn 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 Lekha Chaisorn. Lekha Chaisorn 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 4
3 1
4 1
5
TRECVID 2010 Known-item Search (KIS) Task by I2R.
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7 3
8 2
9 0
10 2
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12 5
13 2
14 1
15 8
16 19
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18 37
19 3
20 55

About Lekha Chaisorn

Lekha Chaisorn is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Artificial Intelligence, having authored 32 papers that have together received 274 indexed citations. Recurring topics across this work include Video Analysis and Summarization (21 papers), Advanced Image and Video Retrieval Techniques (19 papers) and Image Retrieval and Classification Techniques (9 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (245 citations), Signal Processing (102 citations) and Artificial Intelligence (70 citations). Lekha Chaisorn has collaborated with scholars based in Singapore, China and Thailand. Frequent co-authors include Tat‐Seng Chua, Chin‐Hui Lee, Shi-Yong Neo, Shih‐Fu Chang, Winston H. Hsu, Grace Hui Yang, Erwin M. Bakker, Michael S. Lew, Hui Li Tan and Huamin Feng. Their work appears in journals such as Lecture notes in computer science, World Wide Web and Journal of Electrical Engineering and Technology.

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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