M. A. Anusuya
- Artificial Intelligence top 5%
- Signal Processing top 5%
- Computer Vision and Pattern Recognition
- Experimental and Cognitive Psychology
- Physiology
- Co-authors
- Michaël CarlMercedes García-MartínezSrinivas BangaloreM. RavichandranM. Mohammed AsifA. RajaramSandeep SreedharanRohit Hariharan
- Topics
- Speech and Audio Processing (8 papers)Speech Recognition and Synthesis (6 papers)Blind Source Separation Techniques (6 papers)
- Journals
- SHILAP Revista de lepidopterologíaEuropean Heart JournalIEEE Computational Intelligence Magazine
- Partner nations
- IndiaDenmarkUnited States
In The Last Decade
M. A. Anusuya
19 papers receiving 254 citations
Peers
Comparison fields: 5 of 58
- Artificial Intelligence 214
- Signal Processing 179
- Computer Vision and Pattern Recognition 39
- Experimental and Cognitive Psychology 24
- Physiology 18
Countries citing papers authored by M. A. Anusuya
This map shows the geographic impact of M. A. Anusuya'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. A. Anusuya with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites M. A. Anusuya more than expected).
Fields of papers citing papers by M. A. Anusuya
This network shows the impact of papers produced by M. A. Anusuya. 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. A. Anusuya. The network helps show where M. A. Anusuya may publish in the future.
Co-authorship network of co-authors of M. A. Anusuya
This figure shows the co-authorship network connecting the top 25 collaborators of M. A. Anusuya. A scholar is included among the top collaborators of M. A. Anusuya 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. A. Anusuya. M. A. Anusuya 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 | 0 | |
| 3 | 0 | |
| 4 | 1 | |
| 5 | 1 | |
| 6 | 1 | |
| 7 | 5 | |
| 8 | 3 | |
| 9 | 2 | |
| 10 | 4 | |
| 11 | 1 | |
| 12 | Expert System Design to Predict Heart and Diabetes Diseases | 6 |
| 13 | SEECAT: Speech & Eye- tracking Enabled Computer Assisted Translation | 1 |
| 14 | SEECAT: ASR & Eye-tracking Enabled Computer Assisted Translation | 8 |
| 15 | Speaker Independent Kannada Speech Recognition using Vector quantization | 11 |
| 16 | 78 | |
| 17 | 15 | |
| 18 | Superficial Analogies and Differences between the Human Brain and the Computer | 1 |
| 19 | 155 | |
| 20 | 2 |
About M. A. Anusuya
M. A. Anusuya is a scholar working on Signal Processing, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 22 papers that have together received 299 indexed citations. Recurring topics across this work include Speech and Audio Processing (8 papers), Speech Recognition and Synthesis (6 papers) and Blind Source Separation Techniques (6 papers). The work is most often cited by research in Signal Processing (179 citations), Artificial Intelligence (214 citations) and Human-Computer Interaction (17 citations). M. A. Anusuya has collaborated with scholars based in India, Denmark and United States. Frequent co-authors include Michaël Carl, Mercedes García-Martínez, Srinivas Bangalore, M. Ravichandran, M. Mohammed Asif, A. Rajaram, Sandeep Sreedharan and Rohit Hariharan. Their work appears in journals such as SHILAP Revista de lepidopterología, European Heart Journal and IEEE Computational Intelligence Magazine.
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.