Punya Thitimajshima
- Electrical and Electronic Engineering top 1%
- Computer Networks and Communications top 0.2%
- Artificial Intelligence top 1%
- Computational Theory and Mathematics top 2%
- Computer Vision and Pattern Recognition top 5%
- Co-authors
- Claude BerrouAlain Glavieux
- Topics
- Image and Signal Denoising Methods (9 papers)Remote-Sensing Image Classification (5 papers)Advanced Image Fusion Techniques (4 papers)
- Cited by
- Computer Networks and CommunicationsElectrical and Electronic EngineeringArtificial Intelligence
- Journals
- Cell and Tissue ResearchMedical Entomology and ZoologyProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE
In The Last Decade
Punya Thitimajshima
14 papers receiving 4.0k citations
Hit Papers
Peers
Comparison fields: 5 of 58
- Electrical and Electronic Engineering 3.8k
- Computer Networks and Communications 3.6k
- Artificial Intelligence 1.2k
- Computational Theory and Mathematics 286
- Computer Vision and Pattern Recognition 265
Countries citing papers authored by Punya Thitimajshima
This map shows the geographic impact of Punya Thitimajshima'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 Punya Thitimajshima with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Punya Thitimajshima more than expected).
Fields of papers citing papers by Punya Thitimajshima
This network shows the impact of papers produced by Punya Thitimajshima. 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 Punya Thitimajshima. The network helps show where Punya Thitimajshima may publish in the future.
Co-authorship network of co-authors of Punya Thitimajshima
This figure shows the co-authorship network connecting the top 25 collaborators of Punya Thitimajshima. A scholar is included among the top collaborators of Punya Thitimajshima 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 Punya Thitimajshima. Punya Thitimajshima is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 8 | |
| 3 | 2 | |
| 4 | 1 | |
| 5 | Near Shannon limit error-correcting coding and decoding: Turbo-codes. 1breakdown → | 4137 |
| 6 | 20 | |
| 7 | 32 | |
| 8 | 1 | |
| 9 | 1 | |
| 10 | 0 | |
| 11 | 23 | |
| 12 | 11 | |
| 13 | MULTISPECTRAL IMAGE SEGMENTATION USING ART1/ART2 NEURAL NETWORKS | 1 |
| 14 | 0 | |
| 15 | 1 | |
| 16 | 1 |
About Punya Thitimajshima
Punya Thitimajshima is a scholar working on Media Technology, Computer Vision and Pattern Recognition and Computer Graphics and Computer-Aided Design, having authored 16 papers that have together received 4.2k indexed citations. Recurring topics across this work include Image and Signal Denoising Methods (9 papers), Remote-Sensing Image Classification (5 papers) and Advanced Image Fusion Techniques (4 papers). The work is most often cited by research in Computer Networks and Communications (3.6k citations), Electrical and Electronic Engineering (3.8k citations) and Artificial Intelligence (1.2k citations). Punya Thitimajshima has collaborated with scholars based in Thailand and France. Frequent co-authors include Claude Berrou and Alain Glavieux. Their work appears in journals such as Cell and Tissue Research, Medical Entomology and Zoology and Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE.
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.