Pradipta Kumar Nanda
- Computer Vision and Pattern Recognition top 5%
- Biomedical Engineering
- Mechanical Engineering
- Electrical and Electronic Engineering
- Civil and Structural Engineering top 10%
- Co-authors
- S. PandaAshish GhoshBadri Narayan SubudhiPriyadarshi KanungoSubhamoy BhattacharyaAnil Kumar SinghC. SharmaS Gangopadhyay
- Topics
- Medical Image Segmentation Techniques (20 papers)Image Retrieval and Classification Techniques (20 papers)Remote-Sensing Image Classification (15 papers)
In The Last Decade
Pradipta Kumar Nanda
71 papers receiving 796 citations
Peers
Comparison fields: 5 of 107
- Computer Vision and Pattern Recognition 219
- Biomedical Engineering 210
- Mechanical Engineering 136
- Electrical and Electronic Engineering 123
- Civil and Structural Engineering 95
Countries citing papers authored by Pradipta Kumar Nanda
This map shows the geographic impact of Pradipta Kumar Nanda'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 Pradipta Kumar Nanda with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pradipta Kumar Nanda more than expected).
Fields of papers citing papers by Pradipta Kumar Nanda
This network shows the impact of papers produced by Pradipta Kumar Nanda. 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 Pradipta Kumar Nanda. The network helps show where Pradipta Kumar Nanda may publish in the future.
Co-authorship network of co-authors of Pradipta Kumar Nanda
This figure shows the co-authorship network connecting the top 25 collaborators of Pradipta Kumar Nanda. A scholar is included among the top collaborators of Pradipta Kumar Nanda 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 Pradipta Kumar Nanda. Pradipta Kumar Nanda is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 8 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 2 | |
| 6 | 9 | |
| 7 | 0 | |
| 8 | 39 | |
| 9 | 17 | |
| 10 | Proceedings of the Third international conference on Swarm, Evolutionary, and Memetic Computing | 2 |
| 11 | 13 | |
| 12 | 16 | |
| 13 | 2 | |
| 14 | 1 | |
| 15 | Moving Object Detection using Compound Markov Random Field Model | 1 |
| 16 | 3 | |
| 17 | 92 | |
| 18 | 97 | |
| 19 | Color Image Segmentation Using MRF Model and Simulated Annealing | 2 |
| 20 | 13 |
About Pradipta Kumar Nanda
Pradipta Kumar Nanda is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Safety, Risk, Reliability and Quality, having authored 80 papers that have together received 849 indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (20 papers), Image Retrieval and Classification Techniques (20 papers) and Remote-Sensing Image Classification (15 papers). The work is most often cited by research in Fluid Flow and Transfer Processes (91 citations), Computer Vision and Pattern Recognition (219 citations) and Media Technology (63 citations). Pradipta Kumar Nanda has collaborated with scholars based in India, Singapore and Australia. Frequent co-authors include S. Panda, Ashish Ghosh, Badri Narayan Subudhi, Priyadarshi Kanungo, Subhamoy Bhattacharya, Anil Kumar Singh, C. Sharma, S Gangopadhyay, Soumyashree Pany and Amtul Nashim. Their work appears in journals such as The Science of The Total Environment, Expert Systems with Applications and IEEE Access.
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.