Trisha Mittal
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence
- Signal Processing
- Sociology and Political Science
- Experimental and Cognitive Psychology
- Co-authors
- Dinesh ManochaAniket BeraRohan ChandraUttaran BhattacharyaViswanathan SwaminathanJohn CollomosseRitwik SinhaShiv Surya
- Topics
- Generative Adversarial Networks and Image Synthesis (4 papers)Human Pose and Action Recognition (3 papers)Digital Media Forensic Detection (3 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceScientific ReportsIEEE Multimedia
- Partner nations
- United StatesIndia
In The Last Decade
Trisha Mittal
11 papers receiving 223 citations
Peers
Comparison fields: 5 of 37
- Computer Vision and Pattern Recognition 186
- Artificial Intelligence 88
- Signal Processing 38
- Sociology and Political Science 19
- Experimental and Cognitive Psychology 19
Countries citing papers authored by Trisha Mittal
This map shows the geographic impact of Trisha Mittal'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 Trisha Mittal with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Trisha Mittal more than expected).
Fields of papers citing papers by Trisha Mittal
This network shows the impact of papers produced by Trisha Mittal. 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 Trisha Mittal. The network helps show where Trisha Mittal may publish in the future.
Co-authorship network of co-authors of Trisha Mittal
This figure shows the co-authorship network connecting the top 25 collaborators of Trisha Mittal. A scholar is included among the top collaborators of Trisha Mittal 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 Trisha Mittal. Trisha Mittal is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 1 | |
| 3 | 3 | |
| 4 | 1 | |
| 5 | 10 | |
| 6 | 8 | |
| 7 | 17 | |
| 8 | 0 | |
| 9 | 175 | |
| 10 | Emotions Don't Lie: A Deepfake Detection Method using Audio-Visual Affective Cues | 8 |
| 11 | 5 | |
| 12 | 1 |
About Trisha Mittal
Trisha Mittal is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Experimental and Cognitive Psychology, having authored 12 papers that have together received 231 indexed citations. Recurring topics across this work include Generative Adversarial Networks and Image Synthesis (4 papers), Human Pose and Action Recognition (3 papers) and Digital Media Forensic Detection (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (186 citations), Signal Processing (38 citations) and Artificial Intelligence (88 citations). Trisha Mittal has collaborated with scholars based in United States and India. Frequent co-authors include Dinesh Manocha, Aniket Bera, Rohan Chandra, Uttaran Bhattacharya, Viswanathan Swaminathan, John Collomosse, Ritwik Sinha, Shiv Surya, R. Venkatesh Babu and Puneet Mathur. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Scientific Reports and IEEE Multimedia.
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.