Mridul Ghosh
- Computer Vision and Pattern Recognition top 10%
- Radiology, Nuclear Medicine and Imaging
- Artificial Intelligence
- Media Technology
- Cardiology and Cardiovascular Medicine
- Co-authors
- Pranab Kumar DuttaSk Md ObaidullahKaushik RoyHimadri MukherjeeKC SantoshNibaran DasArup RayChandan Chakraborty
- Topics
- Handwritten Text Recognition Techniques (8 papers)Medical Image Segmentation Techniques (3 papers)Vehicle License Plate Recognition (3 papers)
- Cited by
- Computer Vision and Pattern RecognitionMedia TechnologyRadiology, Nuclear Medicine and Imaging
- Partner nations
- IndiaUnited StatesSlovakia
In The Last Decade
Mridul Ghosh
23 papers receiving 173 citations
Peers
Comparison fields: 5 of 63
- Computer Vision and Pattern Recognition 101
- Radiology, Nuclear Medicine and Imaging 42
- Artificial Intelligence 33
- Media Technology 20
- Cardiology and Cardiovascular Medicine 17
Countries citing papers authored by Mridul Ghosh
This map shows the geographic impact of Mridul Ghosh'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 Mridul Ghosh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mridul Ghosh more than expected).
Fields of papers citing papers by Mridul Ghosh
This network shows the impact of papers produced by Mridul Ghosh. 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 Mridul Ghosh. The network helps show where Mridul Ghosh may publish in the future.
Co-authorship network of co-authors of Mridul Ghosh
This figure shows the co-authorship network connecting the top 25 collaborators of Mridul Ghosh. A scholar is included among the top collaborators of Mridul Ghosh 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 Mridul Ghosh. Mridul Ghosh is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 1 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 0 | |
| 6 | 0 | |
| 7 | 10 | |
| 8 | 0 | |
| 9 | 11 | |
| 10 | 13 | |
| 11 | 4 | |
| 12 | 8 | |
| 13 | 6 | |
| 14 | 2 | |
| 15 | 5 | |
| 16 | 3 | |
| 17 | 2 | |
| 18 | 12 | |
| 19 | 1 | |
| 20 | 2 |
About Mridul Ghosh
Mridul Ghosh is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Geology, having authored 28 papers that have together received 182 indexed citations. Recurring topics across this work include Handwritten Text Recognition Techniques (8 papers), Medical Image Segmentation Techniques (3 papers) and Vehicle License Plate Recognition (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (101 citations), Media Technology (20 citations) and Radiology, Nuclear Medicine and Imaging (42 citations). Mridul Ghosh has collaborated with scholars based in India, United States and Slovakia. Frequent co-authors include Pranab Kumar Dutta, Sk Md Obaidullah, Kaushik Roy, Himadri Mukherjee, KC Santosh, Nibaran Das, Arup Ray, Chandan Chakraborty, Jayanta Pal and Xiao‐Zhi Gao. Their work appears in journals such as IEEE Access, Image and Vision Computing and Artificial Intelligence Review.
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.