Boonserm Kijsirikul
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- Face and Expression Recognition 15
- Advanced Neural Network Applications 7
- Artificial Intelligence top 5%
- Text and Document Classification Technologies 11
- Natural Language Processing Techniques 8
- Neural Networks and Applications 8
- Machine Learning and ELM 7
- Topic Modeling 6
- Signal Processing top 10%
- Speech and Audio Processing 5
- Media Technology top 10%
In The Last Decade
Boonserm Kijsirikul
82 papers receiving 718 citations
Peers
Comparison fields: 5 of 125
- Computer Vision and Pattern Recognition 258
- Artificial Intelligence 376
- Signal Processing 74
- Media Technology 48
- Industrial and Manufacturing Engineering 41
Countries citing papers authored by Boonserm Kijsirikul
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
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
The 25 scholars most cited alongside Boonserm Kijsirikul, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 1 | |
| 2 | 2024 | 3 | |
| 3 | 2023 | 9 | |
| 4 | 2023 | 3 | |
| 5 | 2023 | 3 | |
| 6 | 2023 | 18 | |
| 7 | 2023 | 6 | |
| 8 | 2022 | 9 | |
| 9 | 2022 | 16 | |
| 10 | SVM Based Defect Classification of Electronic Board Using Bag of Keypoints | 2015 | 4 |
| 11 | A step towards high quality one-class Collaborative Filtering using online social relationships | 2011 | 1 |
| 12 | 2003 | 7 | |
| 13 | Fuzzy Logic and Genetic Algorithm for Optimizing the Approximate Match of Rules based on Backpropagation Neural Networks. | 2002 | 2 |
| 14 | 2002 | 3 | |
| 15 | 2002 | 2 | |
| 16 | The Effects of Differnet Feature Sets on the Web Page Categorization Problem Using the Iterative Cross-Training Algorithm. | 2001 | 2 |
| 17 | 2001 | 7 | |
| 18 | Comparing Winnow and RIPPER in Thai Named-Entity Identification | 1999 | 3 |
| 19 | Discrimination-based constructive induction of logic programs | 1992 | 20 |
| 20 | Discrimination-based Constructive Induction | 1992 | 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), Natural Language Processing Techniques (8 papers), Neural Networks and Applications (8 papers), Machine Learning and ELM (7 papers), Advanced Neural Network Applications (7 papers), Topic Modeling (6 papers) and Speech and Audio Processing (5 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.