Boonserm Kijsirikul

1.3k citations
85 papers · 764 indexed · h-index 16
Topics
Face and Expression Recognition (15 papers)Text and Document Classification Technologies (11 papers)Natural Language Processing Techniques (8 papers)
Partner nations
ThailandJapanIndia

In The Last Decade

Boonserm Kijsirikul

82 papers receiving 718 citations

Peers

Boonserm Kijsirikul
Comparison fields: 5 of 125
  • Artificial Intelligence 376
  • Computer Vision and Pattern Recognition 258
  • Signal Processing 74
  • Information Systems 64
  • Control and Systems Engineering 49
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Citations per field
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Countries citing papers authored by Boonserm Kijsirikul

Since Specialization
Citations

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

Fields of papers citing papers by Boonserm Kijsirikul

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Boonserm Kijsirikul

This figure shows the co-authorship network connecting the top 25 collaborators of Boonserm Kijsirikul. A scholar is included among the top collaborators of Boonserm Kijsirikul 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 Boonserm Kijsirikul. Boonserm Kijsirikul 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 1
2 3
3 9
4 3
5 3
6 18
7 6
8 9
9 16
10
SVM Based Defect Classification of Electronic Board Using Bag of Keypoints
4
11
A step towards high quality one-class Collaborative Filtering using online social relationships
1
12 7
13
Fuzzy Logic and Genetic Algorithm for Optimizing the Approximate Match of Rules based on Backpropagation Neural Networks.
2
14 3
15 2
16
The Effects of Differnet Feature Sets on the Web Page Categorization Problem Using the Iterative Cross-Training Algorithm.
2
17 7
18
Comparing Winnow and RIPPER in Thai Named-Entity Identification
3
19
Discrimination-based constructive induction of logic programs
20
20
Discrimination-based Constructive Induction
1

About Boonserm Kijsirikul

Boonserm Kijsirikul is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Signal Processing, having authored 85 papers that have together received 764 indexed citations. Recurring topics across this work include Face and Expression Recognition (15 papers), Text and Document Classification Technologies (11 papers) and Natural Language Processing Techniques (8 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (258 citations), Artificial Intelligence (376 citations) and Signal Processing (74 citations). Boonserm Kijsirikul has collaborated with scholars based in Thailand, Japan and India. Frequent co-authors include Yuji Iwahori, Masayuki Numao, Thanaruk Theeramunkong, Nick Cercone, Tu-Bao Ho, Yoshitsugu Hayashi, Nattapong Thammasan, M. K. Bhuyan, Masamichi Shimura and Shinji Fukui. Their work appears in journals such as IEEE Access, Sensors and Sustainability.

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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