Anindya Halder
Impact in
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- Artificial Intelligence in Healthcare
- Artificial Intelligence top 10%
- Imbalanced Data Classification Techniques
- Advanced Clustering Algorithms Research
Papers in
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- Face and Expression Recognition 5
- Medical Image Segmentation Techniques 4
- Image Retrieval and Classification Techniques 3
- Co-authors
- Susmita Ghosh (7 shared papers)Ashish Ghosh (7 shared papers)Moumita Roy (1 shared paper)Utpal Biswas (2 shared papers)Goutam Saha (1 shared paper)Rajat Kumar Pal (1 shared paper)Bimala P. Baruah (2 shared papers)
- Journals
- Applied Soft Computing (3 papers)Engineering Applications of Artificial Intelligence (2 papers)Artificial Intelligence in Medicine (1 paper)Scientific Reports (1 paper)International Journal of Machine Learning and Cybernetics (1 paper)
- Partner nations
- India
In The Last Decade
Anindya Halder
32 papers receiving 383 citations
Peers
Comparison fields: 5 of 84
- Health Information Management 38
- Artificial Intelligence 198
- Media Technology 49
- Computer Vision and Pattern Recognition 85
- Health Informatics 4
Countries citing papers authored by Anindya Halder
This map shows the geographic impact of Anindya Halder'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 Anindya Halder with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Anindya Halder more than expected).
Fields of papers citing papers by Anindya Halder
This network shows the impact of papers produced by Anindya Halder. 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 Anindya Halder. The network helps show where Anindya Halder may publish in the future.
Co-authors
The 8 scholars most cited alongside Anindya Halder, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 38 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 55 | |
| 2 | 2008 | 49 | |
| 3 | 2011 | 41 | |
| 4 | 2021 | 40 | |
| 5 | 2023 | 31 | |
| 6 | 2019 | 24 | |
| 7 | 2013 | 19 | |
| 8 | 2020 | 17 | |
| 9 | 2009 | 16 | |
| 10 | 2019 | 15 | |
| 11 | 2019 | 13 | |
| 12 | 2009 | 12 | |
| 13 | 2014 | 11 | |
| 14 | 2019 | 9 | |
| 15 | 2015 | 7 | |
| 16 | 2020 | 5 | |
| 17 | 2022 | 5 | |
| 18 | 2021 | 4 | |
| 19 | 2024 | 4 | |
| 20 | 2021 | 4 |
About Anindya Halder
Anindya Halder is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Molecular Biology, Computational Theory and Mathematics and Media Technology, having authored 38 papers that have together received 397 indexed citations. Recurring topics across this work include Gene expression and cancer classification (8 papers), Rough Sets and Fuzzy Logic (6 papers), Face and Expression Recognition (5 papers), Brain Tumor Detection and Classification (5 papers), Medical Image Segmentation Techniques (4 papers), Machine Learning in Bioinformatics (3 papers), Insect and Arachnid Ecology and Behavior (3 papers) and Image Retrieval and Classification Techniques (3 papers). The work is most often cited by research in Health Information Management (38 citations), Artificial Intelligence (198 citations), Media Technology (49 citations), Computer Vision and Pattern Recognition (85 citations) and Health Informatics (4 citations). Anindya Halder has collaborated with scholars based in India. Frequent co-authors include Susmita Ghosh, Ashish Ghosh, Moumita Roy, Utpal Biswas, Goutam Saha, Rajat Kumar Pal, Goutam Saha and Bimala P. Baruah. Their work appears in journals such as Applied Soft Computing, Engineering Applications of Artificial Intelligence, Artificial Intelligence in Medicine, Scientific Reports and International Journal of Machine Learning and Cybernetics.
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.