Sounak Dey
- Computer Vision and Pattern Recognition top 10%
- Artificial Intelligence
- Electrical and Electronic Engineering
- Cognitive Neuroscience
- Computer Networks and Communications
- Co-authors
- Arijit MukherjeeRanjan DasguptaAlícia FornésJosep LladósP. BalamuraliUmapada PalJ. Ignacio ToledoPalaiahnakote Shivakumara
- Topics
- Advanced Memory and Neural Computing (10 papers)Neural Networks and Reservoir Computing (9 papers)Handwritten Text Recognition Techniques (6 papers)
- Journals
- SHILAP Revista de lepidopterologíaPattern RecognitionNeurocomputing
In The Last Decade
Sounak Dey
33 papers receiving 212 citations
Peers
Comparison fields: 5 of 58
- Computer Vision and Pattern Recognition 92
- Artificial Intelligence 90
- Electrical and Electronic Engineering 69
- Cognitive Neuroscience 30
- Computer Networks and Communications 28
Countries citing papers authored by Sounak Dey
This map shows the geographic impact of Sounak Dey'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 Sounak Dey with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sounak Dey more than expected).
Fields of papers citing papers by Sounak Dey
This network shows the impact of papers produced by Sounak Dey. 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 Sounak Dey. The network helps show where Sounak Dey may publish in the future.
Co-authorship network of co-authors of Sounak Dey
This figure shows the co-authorship network connecting the top 25 collaborators of Sounak Dey. A scholar is included among the top collaborators of Sounak Dey 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 Sounak Dey. Sounak Dey is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 14 | |
| 2 | 1 | |
| 3 | 4 | |
| 4 | 6 | |
| 5 | 8 | |
| 6 | 9 | |
| 7 | 13 | |
| 8 | 10 | |
| 9 | 2 | |
| 10 | 7 | |
| 11 | 2 | |
| 12 | 26 | |
| 13 | 8 | |
| 14 | 1 | |
| 15 | 17 | |
| 16 | 4 | |
| 17 | 4 | |
| 18 | Facilitating Scientific Research through Workflows and Provenance on the DataONE Cyberinfrastructure (Invited) | 1 |
| 19 | 8 | |
| 20 | 1 |
About Sounak Dey
Sounak Dey is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Cognitive Neuroscience, having authored 33 papers that have together received 232 indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (10 papers), Neural Networks and Reservoir Computing (9 papers) and Handwritten Text Recognition Techniques (6 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (92 citations), Media Technology (25 citations) and Artificial Intelligence (90 citations). Sounak Dey has collaborated with scholars based in India, Spain and Malaysia. Frequent co-authors include Arijit Mukherjee, Ranjan Dasgupta, Alícia Fornés, Josep Lladós, P. Balamurali, Umapada Pal, J. Ignacio Toledo, Palaiahnakote Shivakumara, Arpan Pal and Tong Lü. Their work appears in journals such as SHILAP Revista de lepidopterología, Pattern Recognition and Neurocomputing.
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.