N. Srinivasa
- Electrical and Electronic Engineering
- Computer Vision and Pattern Recognition top 5%
- Cognitive Neuroscience top 10%
- Artificial Intelligence top 10%
- Cellular and Molecular Neuroscience
- Co-authors
- Jose Cruz-AlbrechtJohn C. ZiegertY. OwechkoJean PonceAttawith SudsangK.R. RamakrishnanRajeev SharmaYoungkwan Cho
- Topics
- Advanced Vision and Imaging (8 papers)Neural Networks and Applications (6 papers)Video Surveillance and Tracking Methods (6 papers)
- Cited by
- Computer Vision and Pattern RecognitionCognitive NeuroscienceCellular and Molecular Neuroscience
- Journals
- IEEE Transactions on Signal ProcessingIEEE Transactions on Medical ImagingIEEE Transactions on Neural Networks and Learning Systems
- Partner nations
- United StatesIndia
In The Last Decade
N. Srinivasa
33 papers receiving 571 citations
Peers
Comparison fields: 5 of 73
- Electrical and Electronic Engineering 252
- Computer Vision and Pattern Recognition 194
- Cognitive Neuroscience 154
- Artificial Intelligence 131
- Cellular and Molecular Neuroscience 122
Countries citing papers authored by N. Srinivasa
This map shows the geographic impact of N. Srinivasa'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 N. Srinivasa with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites N. Srinivasa more than expected).
Fields of papers citing papers by N. Srinivasa
This network shows the impact of papers produced by N. Srinivasa. 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 N. Srinivasa. The network helps show where N. Srinivasa may publish in the future.
Co-authorship network of co-authors of N. Srinivasa
This figure shows the co-authorship network connecting the top 25 collaborators of N. Srinivasa. A scholar is included among the top collaborators of N. Srinivasa 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 N. Srinivasa. N. Srinivasa is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 38 | |
| 2 | 14 | |
| 3 | 164 | |
| 4 | 14 | |
| 5 | 4 | |
| 6 | 3 | |
| 7 | 27 | |
| 8 | 9 | |
| 9 | 16 | |
| 10 | 2 | |
| 11 | 16 | |
| 12 | On Detecting Edges from Projection Data | 0 |
| 13 | 12 | |
| 14 | 13 | |
| 15 | 9 | |
| 16 | 37 | |
| 17 | 5 | |
| 18 | 29 | |
| 19 | 6 | |
| 20 | Image Reconstruction Form Truncated Projections : A Linear Predication Approach | 1 |
About N. Srinivasa
N. Srinivasa is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Media Technology, having authored 35 papers that have together received 597 indexed citations. Recurring topics across this work include Advanced Vision and Imaging (8 papers), Neural Networks and Applications (6 papers) and Video Surveillance and Tracking Methods (6 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (194 citations), Cognitive Neuroscience (154 citations) and Cellular and Molecular Neuroscience (122 citations). N. Srinivasa has collaborated with scholars based in United States and India. Frequent co-authors include Jose Cruz-Albrecht, John C. Ziegert, Y. Owechko, Jean Ponce, Attawith Sudsang, K.R. Ramakrishnan, Rajeev Sharma, Youngkwan Cho, Narendra Ahuja and Musa Jouaneh. Their work appears in journals such as IEEE Transactions on Signal Processing, IEEE Transactions on Medical Imaging and IEEE Transactions on Neural Networks and Learning Systems.
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.