Sanjay N. Talbar
- Computer Vision and Pattern Recognition top 1%
- Radiology, Nuclear Medicine and Imaging top 2%
- Artificial Intelligence top 2%
- Pulmonary and Respiratory Medicine top 10%
- Biomedical Engineering
- Co-authors
- Suhas GajreBhakti BahetiUjjwal BaidShubham InnaniAbhishek MahajanMeenakshi ThakurShweta TyagiSatishkumar Chavan
- Topics
- Radiomics and Machine Learning in Medical Imaging (19 papers)Image Retrieval and Classification Techniques (14 papers)AI in cancer detection (14 papers)
- Journals
- SHILAP Revista de lepidopterologíaScientific ReportsACM Computing Surveys
In The Last Decade
Sanjay N. Talbar
108 papers receiving 1.9k citations
Peers
Comparison fields: 5 of 130
- Computer Vision and Pattern Recognition 849
- Radiology, Nuclear Medicine and Imaging 687
- Artificial Intelligence 485
- Pulmonary and Respiratory Medicine 314
- Biomedical Engineering 200
Countries citing papers authored by Sanjay N. Talbar
This map shows the geographic impact of Sanjay N. Talbar'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 Sanjay N. Talbar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sanjay N. Talbar more than expected).
Fields of papers citing papers by Sanjay N. Talbar
This network shows the impact of papers produced by Sanjay N. Talbar. 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 Sanjay N. Talbar. The network helps show where Sanjay N. Talbar may publish in the future.
Co-authorship network of co-authors of Sanjay N. Talbar
This figure shows the co-authorship network connecting the top 25 collaborators of Sanjay N. Talbar. A scholar is included among the top collaborators of Sanjay N. Talbar 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 Sanjay N. Talbar. Sanjay N. Talbar is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 6 | |
| 2 | 1 | |
| 3 | 43 | |
| 4 | 49 | |
| 5 | 100 | |
| 6 | 9 | |
| 7 | 64 | |
| 8 | 77 | |
| 9 | 165 | |
| 10 | 2 | |
| 11 | 21 | |
| 12 | 31 | |
| 13 | 60 | |
| 14 | 3 | |
| 15 | 17 | |
| 16 | 11 | |
| 17 | 22 | |
| 18 | 10 | |
| 19 | Image adaptive watermarking using fuzzy logic on FPGA | 2 |
| 20 | Hybrid machine learning approach for object recognition: fusion of features and decisions | 1 |
About Sanjay N. Talbar
Sanjay N. Talbar is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Signal Processing, having authored 116 papers that have together received 2.0k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (19 papers), Image Retrieval and Classification Techniques (14 papers) and AI in cancer detection (14 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (849 citations), Radiology, Nuclear Medicine and Imaging (687 citations) and Neurology (197 citations). Sanjay N. Talbar has collaborated with scholars based in India, Nepal and Malaysia. Frequent co-authors include Suhas Gajre, Bhakti Baheti, Ujjwal Baid, Shubham Innani, Abhishek Mahajan, Meenakshi Thakur, Shweta Tyagi, Satishkumar Chavan, Meenakshi M. Pawar and Nilesh Sable. Their work appears in journals such as SHILAP Revista de lepidopterología, Scientific Reports and ACM Computing Surveys.
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.