Mrinal Bachute
Impact in
- Automotive Engineering top 10%
- Autonomous Vehicle Technology and Safety
Papers in
-
- Speech and Audio Processing 5
- Blind Source Separation Techniques 3
- Co-authors
- Ketan Kotecha (7 shared papers)Shilpa Gite (4 shared papers)Mazen E. Assiri (1 shared paper)Biswajeet Pradhan (2 shared papers)V. Vijayakumar (1 shared paper)IS Amiri (1 shared paper)G. Palai (1 shared paper)Vinayak K. Bairagi (2 shared papers)
In The Last Decade
Mrinal Bachute
22 papers receiving 303 citations
Peers
Comparison fields: 5 of 99
- Health Informatics 10
- Automotive Engineering 69
- Computer Vision and Pattern Recognition 69
- Artificial Intelligence 93
- Neurology 21
Countries citing papers authored by Mrinal Bachute
This map shows the geographic impact of Mrinal Bachute'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 Mrinal Bachute with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mrinal Bachute more than expected).
Fields of papers citing papers by Mrinal Bachute
This network shows the impact of papers produced by Mrinal Bachute. 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 Mrinal Bachute. The network helps show where Mrinal Bachute may publish in the future.
Co-authors
The 24 scholars most cited alongside Mrinal Bachute, 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 30 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 155 | |
| 2 | 2022 | 60 | |
| 3 | 2023 | 20 | |
| 4 | 2022 | 19 | |
| 5 | 2015 | 12 | |
| 6 | 2022 | 12 | |
| 7 | 2021 | 11 | |
| 8 | 2021 | 6 | |
| 9 | 2021 | 6 | |
| 10 | 2024 | 3 | |
| 11 | 2019 | 2 | |
| 12 | Performance Analysis and Comparison of Complex LMS, Sign LMS and RLS Algorithms for Speech Enhancement Application | 2017 | 2 |
| 13 | 2025 | 2 | |
| 14 | 2016 | 2 | |
| 15 | 2024 | 1 | |
| 16 | 2024 | 1 | |
| 17 | 2025 | 1 | |
| 18 | 2025 | 1 | |
| 19 | 2024 | 1 | |
| 20 | Removing the noise from X-ray image using Image processing Technology: A Bibliometric Survey and Future Research Directions | 2021 | 1 |
About Mrinal Bachute
Mrinal Bachute is a scholar working on Artificial Intelligence, Signal Processing, Computer Vision and Pattern Recognition, Electrical and Electronic Engineering and Biomedical Engineering, having authored 30 papers that have together received 320 indexed citations. Recurring topics across this work include Speech and Audio Processing (5 papers), Autonomous Vehicle Technology and Safety (3 papers), Advanced Neural Network Applications (3 papers), Network Security and Intrusion Detection (3 papers), Advanced Chemical Sensor Technologies (3 papers), Advanced Adaptive Filtering Techniques (3 papers), Blind Source Separation Techniques (3 papers) and Spectroscopy and Chemometric Analyses (2 papers). The work is most often cited by research in Health Informatics (10 citations), Automotive Engineering (69 citations), Computer Vision and Pattern Recognition (69 citations), Artificial Intelligence (93 citations) and Neurology (21 citations). Mrinal Bachute has collaborated with scholars based in India, Australia and Thailand. Frequent co-authors include Ketan Kotecha, Shilpa Gite, Mazen E. Assiri, Biswajeet Pradhan, V. Vijayakumar, IS Amiri, G. Palai, Vinayak K. Bairagi, Ekkarat Boonchieng and Bibhuti Bhusan Dash. Their work appears in journals such as IEEE Access, Scientific Reports, Biomedical Signal Processing and Control, Computer Modeling in Engineering & Sciences and Future Internet.
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.