Debi Prosad Dogra
- Human-Computer Interaction top 0.2%
- Hand Gesture Recognition Systems 19
- Gaze Tracking and Assistive Technology 9
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- Video Surveillance and Tracking Methods 30
- Human Pose and Action Recognition 22
- Advanced Image and Video Retrieval Techniques 11
- Video Analysis and Summarization 9
- Cognitive Neuroscience top 2%
- EEG and Brain-Computer Interfaces 17
- Signal Processing top 2%
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- Anomaly Detection Techniques and Applications 22
- Co-authors
- Partha Pratim RoyPradeep KumarRajkumar SainiByung‐Gyu KimSamarjit KarDebashis Das ChakladarPallavi KaushikHeeseung Choi
- Journals
- Expert Systems with Applications (8 papers)IEEE Transactions on Biomedical Engineering (1 paper)ACM Computing Surveys (2 papers)
- Partner nations
- IndiaSouth KoreaUnited Arab Emirates
In The Last Decade
Debi Prosad Dogra
103 papers receiving 2.6k citations
Peers
Comparison fields: 5 of 136
- Human-Computer Interaction 827
- Computer Vision and Pattern Recognition 1.1k
- Cognitive Neuroscience 687
- Signal Processing 267
- Developmental and Educational Psychology 279
Countries citing papers authored by Debi Prosad Dogra
This map shows the geographic impact of Debi Prosad Dogra'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 Debi Prosad Dogra with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Debi Prosad Dogra more than expected).
Fields of papers citing papers by Debi Prosad Dogra
This network shows the impact of papers produced by Debi Prosad Dogra. 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 Debi Prosad Dogra. The network helps show where Debi Prosad Dogra may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Debi Prosad Dogra, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2023 | 1 | |
| 2 | 2023 | 20 | |
| 3 | 2022 | 6 | |
| 4 | 2022 | 2 | |
| 5 | 2021 | 19 | |
| 6 | 2021 | 45 | |
| 7 | 2021 | 39 | |
| 8 | 2019 | 29 | |
| 9 | 2019 | 72 | |
| 10 | 2019 | 29 | |
| 11 | 2019 | 15 | |
| 12 | 2018 | 19 | |
| 13 | 2018 | 14 | |
| 14 | 2018 | 67 | |
| 15 | 2018 | 16 | |
| 16 | 2018 | 20 | |
| 17 | 2017 | 24 | |
| 18 | 2017 | 147 | |
| 19 | 2017 | 20 | |
| 20 | 2016 | 28 |
About Debi Prosad Dogra
Debi Prosad Dogra is a scholar working on Human-Computer Interaction, Computer Vision and Pattern Recognition and Signal Processing, having authored 105 papers that have together received 2.6k indexed citations. Recurring topics across this work include Video Surveillance and Tracking Methods (30 papers), Anomaly Detection Techniques and Applications (22 papers), Human Pose and Action Recognition (22 papers), Hand Gesture Recognition Systems (19 papers), EEG and Brain-Computer Interfaces (17 papers), Advanced Image and Video Retrieval Techniques (11 papers), Video Analysis and Summarization (9 papers) and Gaze Tracking and Assistive Technology (9 papers). The work is most often cited by research in Human-Computer Interaction (827 citations), Computer Vision and Pattern Recognition (1.1k citations) and Cognitive Neuroscience (687 citations). Debi Prosad Dogra has collaborated with scholars based in India, South Korea and United Arab Emirates. Frequent co-authors include Partha Pratim Roy, Pradeep Kumar, Rajkumar Saini, Byung‐Gyu Kim, Samarjit Kar, Debashis Das Chakladar, Pallavi Kaushik, Heeseung Choi, Arif Ahmed Sekh and Ig-Jae Kim. Their work appears in journals such as Expert Systems with Applications, IEEE Transactions on Biomedical Engineering and ACM Computing Surveys.
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.