Rig Das
Impact in
- Signal Processing top 5%
- Biometric Identification and Security
- Cognitive Neuroscience top 5%
- EEG and Brain-Computer Interfaces
- Neural dynamics and brain function
Papers in
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- EEG and Brain-Computer Interfaces 10
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- Advanced Steganography and Watermarking Techniques 4
- Digital Media Forensic Detection 4
- Chaos-based Image/Signal Encryption 3
- Co-authors
- Emanuele Maiorana (7 shared papers)Patrizio Campisi (7 shared papers)Emanuela Piciucco (2 shared papers)Muhammad Ahmed Khan (7 shared papers)Sadasivan Puthusserypady (7 shared papers)Helle K. Iversen (2 shared papers)Themrichon Tuithung (2 shared papers)Iris Brunner (2 shared papers)
In The Last Decade
Rig Das
22 papers receiving 799 citations
Rig Das's Hit Papers
Peers
Comparison fields: 5 of 82
- Signal Processing 262
- Cognitive Neuroscience 373
- Human-Computer Interaction 76
- Computer Vision and Pattern Recognition 217
- Cellular and Molecular Neuroscience 129
Countries citing papers authored by Rig Das
This map shows the geographic impact of Rig Das'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 Rig Das with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rig Das more than expected).
Fields of papers citing papers by Rig Das
This network shows the impact of papers produced by Rig Das. 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 Rig Das. The network helps show where Rig Das may publish in the future.
Co-authors
The 25 scholars most cited alongside Rig Das, 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 23 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Convolutional Neural Network for Finger-Vein-Based Biometric Identification Hit paper breakdown → | 2018 | 247 |
| 2 | 2020 | 187 | |
| 3 | 2016 | 73 | |
| 4 | 2012 | 62 | |
| 5 | Deep Learning Advances on Different 3D Data Representations: A Survey. | 2018 | 41 |
| 6 | 2018 | 38 | |
| 7 | 2017 | 31 | |
| 8 | 2015 | 27 | |
| 9 | 2021 | 22 | |
| 10 | 2021 | 13 | |
| 11 | 2016 | 12 | |
| 12 | 2020 | 12 | |
| 13 | 2022 | 11 | |
| 14 | 2021 | 9 | |
| 15 | 2016 | 6 | |
| 16 | 2014 | 6 | |
| 17 | 2022 | 5 | |
| 18 | 2021 | 5 | |
| 19 | 2023 | 4 | |
| 20 | 2014 | 4 |
About Rig Das
Rig Das is a scholar working on Cognitive Neuroscience, Computer Vision and Pattern Recognition, Human-Computer Interaction, Cellular and Molecular Neuroscience and Rehabilitation, having authored 23 papers that have together received 820 indexed citations. Recurring topics across this work include EEG and Brain-Computer Interfaces (10 papers), Gaze Tracking and Assistive Technology (5 papers), Muscle activation and electromyography studies (4 papers), Advanced Steganography and Watermarking Techniques (4 papers), Digital Media Forensic Detection (4 papers), Neuroscience and Neural Engineering (4 papers), Stroke Rehabilitation and Recovery (4 papers) and Chaos-based Image/Signal Encryption (3 papers). The work is most often cited by research in Signal Processing (262 citations), Cognitive Neuroscience (373 citations), Human-Computer Interaction (76 citations), Computer Vision and Pattern Recognition (217 citations) and Cellular and Molecular Neuroscience (129 citations). Rig Das has collaborated with scholars based in Italy, Denmark and India. Frequent co-authors include Emanuele Maiorana, Patrizio Campisi, Emanuela Piciucco, Muhammad Ahmed Khan, Sadasivan Puthusserypady, Helle K. Iversen, Themrichon Tuithung, Iris Brunner, Daria La Rocca and Gleb Gusev. Their work appears in journals such as Journal of Clinical Sleep Medicine, Sleep Medicine, IEEE Signal Processing Letters, Journal of Neural Engineering and Nutrition Metabolism and Cardiovascular Diseases.
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.