M. H. Supriya
- Computer Vision and Pattern Recognition top 5%
- Oceanography top 5%
- Signal Processing top 5%
- Ocean Engineering top 5%
- Experimental and Cognitive Psychology top 10%
- Co-authors
- Suraj KamalArun A. BalakrishnanAbdul MujeebK. MohankumarChander PrabhaK. Poulose JacobDivya BijukumarDidem Ozevin
- Topics
- Underwater Acoustics Research (33 papers)Underwater Vehicles and Communication Systems (17 papers)Blind Source Separation Techniques (16 papers)
- Journals
- SHILAP Revista de lepidopterologíaThe Journal of the Acoustical Society of AmericaIEEE Signal Processing Letters
- Partner nations
- IndiaChinaUnited States
In The Last Decade
M. H. Supriya
66 papers receiving 565 citations
Peers
Comparison fields: 5 of 87
- Computer Vision and Pattern Recognition 280
- Oceanography 156
- Signal Processing 135
- Ocean Engineering 95
- Experimental and Cognitive Psychology 91
Countries citing papers authored by M. H. Supriya
This map shows the geographic impact of M. H. Supriya'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 M. H. Supriya with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites M. H. Supriya more than expected).
Fields of papers citing papers by M. H. Supriya
This network shows the impact of papers produced by M. H. Supriya. 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 M. H. Supriya. The network helps show where M. H. Supriya may publish in the future.
Co-authorship network of co-authors of M. H. Supriya
This figure shows the co-authorship network connecting the top 25 collaborators of M. H. Supriya. A scholar is included among the top collaborators of M. H. Supriya 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 M. H. Supriya. M. H. Supriya 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 | 1 | |
| 4 | 0 | |
| 5 | 4 | |
| 6 | 1 | |
| 7 | 0 | |
| 8 | 6 | |
| 9 | 2 | |
| 10 | 23 | |
| 11 | 63 | |
| 12 | 3 | |
| 13 | HARDWARE REALIZATION OF CANNY EDGE DETECTION ALGORITHM FOR UNDERWATER IMAGE SEGMENTATION USING FIELD PROGRAMMABLE GATE ARRAYS | 9 |
| 14 | Spam: A Big Data Challenge | 1 |
| 15 | 1 | |
| 16 | 8 | |
| 17 | 10 | |
| 18 | 1 | |
| 19 | 4 | |
| 20 | Implementation of an Intelligent TargetClassifier with Bicoherence Feature Set | 1 |
About M. H. Supriya
M. H. Supriya is a scholar working on Oceanography, Signal Processing and Computer Vision and Pattern Recognition, having authored 75 papers that have together received 605 indexed citations. Recurring topics across this work include Underwater Acoustics Research (33 papers), Underwater Vehicles and Communication Systems (17 papers) and Blind Source Separation Techniques (16 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (280 citations), Oceanography (156 citations) and Signal Processing (135 citations). M. H. Supriya has collaborated with scholars based in India, China and United States. Frequent co-authors include Suraj Kamal, Arun A. Balakrishnan, Abdul Mujeeb, K. Mohankumar, Chander Prabha, K. Poulose Jacob, Divya Bijukumar, Didem Ozevin, Mathew T. Mathew and Sheng‐Wei Chi. Their work appears in journals such as SHILAP Revista de lepidopterología, The Journal of the Acoustical Society of America and IEEE Signal Processing Letters.
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.