Himashi Peiris
Impact in
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- Medical Image Segmentation Techniques
- Advanced Neural Network Applications
Papers in
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- Advanced Neural Network Applications 2
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- Radiomics and Machine Learning in Medical Imaging 2
- Advanced Neuroimaging Techniques and Applications 1
- COVID-19 diagnosis using AI 1
- MRI in cancer diagnosis 1
- Co-authors
- Mehrtash Harandi (4 shared papers)Zhaolin Chen (3 shared papers)Gary F. Egan (4 shared papers)Munawar Hayat (1 shared paper)Mehrdad Arashpour (1 shared paper)Jianfei Cai (1 shared paper)Numan Kutaiba (1 shared paper)Stefan R. Kachel (1 shared paper)
- Journals
- Nature Machine Intelligence (1 paper)Resources Conservation and Recycling (1 paper)NMR in Biomedicine (1 paper)Neurocomputing (1 paper)International Journal of Engineering & Technology (1 paper)
In The Last Decade
Himashi Peiris
4 papers receiving 68 citations
Peers
Comparison fields: 5 of 32
- Nuclear Energy and Engineering 1
- Computer Vision and Pattern Recognition 29
- Neurology 11
- Industrial and Manufacturing Engineering 7
- Building and Construction 11
Countries citing papers authored by Himashi Peiris
This map shows the geographic impact of Himashi Peiris'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 Himashi Peiris with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Himashi Peiris more than expected).
Fields of papers citing papers by Himashi Peiris
This network shows the impact of papers produced by Himashi Peiris. 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 Himashi Peiris. The network helps show where Himashi Peiris may publish in the future.
Co-authors
The 20 scholars most cited alongside Himashi Peiris, 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 | 2023 | 54 | |
| 2 | 2024 | 13 | |
| 3 | 2025 | 1 | |
| 4 | 2025 | 1 | |
| 5 | 2018 | 1 | |
| 6 | 2025 | 0 | |
| 7 | 2025 | 0 |
About Himashi Peiris
Himashi Peiris is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Artificial Intelligence, Civil and Structural Engineering and Control and Systems Engineering, having authored 7 papers that have together received 70 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (2 papers), Advanced Neural Network Applications (2 papers), Advanced Neuroimaging Techniques and Applications (1 paper), Hepatocellular Carcinoma Treatment and Prognosis (1 paper), Domain Adaptation and Few-Shot Learning (1 paper), COVID-19 diagnosis using AI (1 paper), Robotics and Automated Systems (1 paper) and MRI in cancer diagnosis (1 paper). The work is most often cited by research in Nuclear Energy and Engineering (1 citation), Computer Vision and Pattern Recognition (29 citations), Neurology (11 citations), Industrial and Manufacturing Engineering (7 citations) and Building and Construction (11 citations). Himashi Peiris has collaborated with scholars based in Australia and China. Frequent co-authors include Mehrtash Harandi, Zhaolin Chen, Gary F. Egan, Munawar Hayat, Mehrdad Arashpour, Jianfei Cai, Numan Kutaiba, Stefan R. Kachel, Meng Law and Anthony Tran. Their work appears in journals such as Nature Machine Intelligence, Resources Conservation and Recycling, NMR in Biomedicine, Neurocomputing and International Journal of Engineering & 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.