Mahesh Pawar
- Artificial Intelligence
- Computer Vision and Pattern Recognition top 10%
- Neurology
- Radiology, Nuclear Medicine and Imaging
- Health Information Management top 5%
- Co-authors
- Piyush Kumar ShuklaAnjana PandeySachin GoyalSandeep KakdeSoumya Ranjan NayakWaleed S. AlnumayUttam GhoshManoj Kumar
- Topics
- Brain Tumor Detection and Classification (5 papers)Vehicle License Plate Recognition (5 papers)Digital Imaging for Blood Diseases (4 papers)
- Journals
- Neural Computing and ApplicationsMultimedia Tools and ApplicationsArtificial Intelligence in Medicine
- Partner nations
- IndiaUnited Arab EmiratesSaudi Arabia
In The Last Decade
Mahesh Pawar
20 papers receiving 218 citations
Peers
Comparison fields: 5 of 71
- Artificial Intelligence 79
- Computer Vision and Pattern Recognition 69
- Neurology 63
- Radiology, Nuclear Medicine and Imaging 52
- Health Information Management 35
Countries citing papers authored by Mahesh Pawar
This map shows the geographic impact of Mahesh Pawar'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 Mahesh Pawar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mahesh Pawar more than expected).
Fields of papers citing papers by Mahesh Pawar
This network shows the impact of papers produced by Mahesh Pawar. 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 Mahesh Pawar. The network helps show where Mahesh Pawar may publish in the future.
Co-authorship network of co-authors of Mahesh Pawar
This figure shows the co-authorship network connecting the top 25 collaborators of Mahesh Pawar. A scholar is included among the top collaborators of Mahesh Pawar 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 Mahesh Pawar. Mahesh Pawar is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 36 | |
| 4 | 18 | |
| 5 | 3 | |
| 6 | 7 | |
| 7 | 2 | |
| 8 | 25 | |
| 9 | 36 | |
| 10 | 0 | |
| 11 | 0 | |
| 12 | A Survey on Community Detection Algorithm and Its Applications | 2 |
| 13 | 36 | |
| 14 | Smart Voice Controlled Vehicle with Obstacle Detection Using IoT | 0 |
| 15 | Predicting Student’s Performance Using Data Mining Techniques: A Survey From 2002 To 2020 | 0 |
| 16 | Robotic Process Automation: The Virtual Workforce | 7 |
| 17 | 16 | |
| 18 | 1 | |
| 19 | 3 | |
| 20 | 9 |
About Mahesh Pawar
Mahesh Pawar is a scholar working on Health Information Management, Health Informatics and Neurology, having authored 25 papers that have together received 230 indexed citations. Recurring topics across this work include Brain Tumor Detection and Classification (5 papers), Vehicle License Plate Recognition (5 papers) and Digital Imaging for Blood Diseases (4 papers). The work is most often cited by research in Health Informatics (11 citations), Neurology (63 citations) and Health Information Management (35 citations). Mahesh Pawar has collaborated with scholars based in India, United Arab Emirates and Saudi Arabia. Frequent co-authors include Piyush Kumar Shukla, Anjana Pandey, Sachin Goyal, Sandeep Kakde, Soumya Ranjan Nayak, Waleed S. Alnumay, Uttam Ghosh, Manoj Kumar, Akhil V. Nakhate and Paras Jain. Their work appears in journals such as Neural Computing and Applications, Multimedia Tools and Applications and Artificial Intelligence in Medicine.
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.