Mohan Karnati
Impact in
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- Emotion and Mood Recognition
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- Face and Expression Recognition
- Face recognition and analysis
Papers in
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- Face and Expression Recognition 7
- Face recognition and analysis 4
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- AI in cancer detection 6
- Co-authors
- Ayan Seal (12 shared papers)Ondřej Krejcar (11 shared papers)Anis Yazidi (7 shared papers)Geet Sahu (8 shared papers)Debotosh Bhattacharjee (1 shared paper)Malay Kishore Dutta (8 shared papers)Ritesh Maurya (7 shared papers)Abhishek Gupta (2 shared papers)
In The Last Decade
Mohan Karnati
25 papers receiving 588 citations
Mohan Karnati's Hit Papers
Peers
Comparison fields: 5 of 63
- Experimental and Cognitive Psychology 308
- Computer Vision and Pattern Recognition 324
- Human-Computer Interaction 39
- Cognitive Neuroscience 125
- Urban Studies 28
Countries citing papers authored by Mohan Karnati
This map shows the geographic impact of Mohan Karnati'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 Mohan Karnati with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mohan Karnati more than expected).
Fields of papers citing papers by Mohan Karnati
This network shows the impact of papers produced by Mohan Karnati. 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 Mohan Karnati. The network helps show where Mohan Karnati may publish in the future.
Co-authors
The 17 scholars most cited alongside Mohan Karnati, 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 27 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 134 | |
| 2 | 2021 | 97 | |
| 3 | Understanding Deep Learning Techniques for Recognition of Human Emotions Using Facial Expressions: A Comprehensive Survey Hit paper breakdown → | 2023 | 92 |
| 4 | 2021 | 57 | |
| 5 | 2022 | 55 | |
| 6 | 2022 | 32 | |
| 7 | 2022 | 28 | |
| 8 | 2023 | 23 | |
| 9 | 2024 | 22 | |
| 10 | 2023 | 20 | |
| 11 | 2023 | 16 | |
| 12 | 2024 | 5 | |
| 13 | 2024 | 5 | |
| 14 | 2023 | 4 | |
| 15 | 2023 | 3 | |
| 16 | 2023 | 3 | |
| 17 | 2024 | 2 | |
| 18 | 2024 | 2 | |
| 19 | 2023 | 2 | |
| 20 | 2025 | 1 |
About Mohan Karnati
Mohan Karnati is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Cognitive Neuroscience and Experimental and Cognitive Psychology, having authored 27 papers that have together received 609 indexed citations. Recurring topics across this work include Face and Expression Recognition (7 papers), AI in cancer detection (6 papers), EEG and Brain-Computer Interfaces (6 papers), Emotion and Mood Recognition (5 papers), COVID-19 diagnosis using AI (4 papers), Face recognition and analysis (4 papers), Radiomics and Machine Learning in Medical Imaging (4 papers) and ECG Monitoring and Analysis (3 papers). The work is most often cited by research in Experimental and Cognitive Psychology (308 citations), Computer Vision and Pattern Recognition (324 citations), Human-Computer Interaction (39 citations), Cognitive Neuroscience (125 citations) and Urban Studies (28 citations). Mohan Karnati has collaborated with scholars based in India, Czechia and Norway. Frequent co-authors include Ayan Seal, Ondřej Krejcar, Anis Yazidi, Geet Sahu, Debotosh Bhattacharjee, Malay Kishore Dutta, Ritesh Maurya, Abhishek Gupta, Joanna Jaworek-Korjakowska and Rishabh Bajpai. Their work appears in journals such as IEEE Transactions on Instrumentation and Measurement, IEEE Transactions on Cognitive and Developmental Systems, Biomedical Signal Processing and Control, Scientific Reports and Applied Intelligence.
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.