Yogesh Singh Rawat
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 10%
- Cognitive Neuroscience
- Information Systems
- Biomedical Engineering
- Co-authors
- Mubarak ShahMohan KankanhalliConcetto SpampinatoAkash KumarMamshad Nayeem RizveVibhav VineetShruti VyasMingli Song
- Topics
- Human Pose and Action Recognition (18 papers)Multimodal Machine Learning Applications (13 papers)Anomaly Detection Techniques and Applications (12 papers)
- Journals
- ACM Computing SurveysIEEE Transactions on Circuits and Systems for Video TechnologyIEEE Transactions on Multimedia
- Partner nations
- United StatesSingaporeIndia
In The Last Decade
Yogesh Singh Rawat
35 papers receiving 431 citations
Peers
Comparison fields: 5 of 77
- Computer Vision and Pattern Recognition 292
- Artificial Intelligence 173
- Cognitive Neuroscience 62
- Information Systems 44
- Biomedical Engineering 20
Countries citing papers authored by Yogesh Singh Rawat
This map shows the geographic impact of Yogesh Singh Rawat'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 Yogesh Singh Rawat with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yogesh Singh Rawat more than expected).
Fields of papers citing papers by Yogesh Singh Rawat
This network shows the impact of papers produced by Yogesh Singh Rawat. 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 Yogesh Singh Rawat. The network helps show where Yogesh Singh Rawat may publish in the future.
Co-authorship network of co-authors of Yogesh Singh Rawat
This figure shows the co-authorship network connecting the top 25 collaborators of Yogesh Singh Rawat. A scholar is included among the top collaborators of Yogesh Singh Rawat 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 Yogesh Singh Rawat. Yogesh Singh Rawat is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 2 | |
| 5 | 3 | |
| 6 | 3 | |
| 7 | 2 | |
| 8 | 1 | |
| 9 | 1 | |
| 10 | 21 | |
| 11 | 76 | |
| 12 | Reformulating Zero-shot Action Recognition for Multi-label Actions | 4 |
| 13 | 47 | |
| 14 | 7 | |
| 15 | Gabriella: An Online System for Real-Time Activity Detection in Untrimmed Surveillance Videos | 1 |
| 16 | UCF-System: Activity Detection in Untrimmed Videos. | 1 |
| 17 | An Online System for Real-Time Activity Detection in Untrimmed Surveillance Videos. | 2 |
| 18 | 4 | |
| 19 | Action and Object Detection for TRECVID. | 1 |
| 20 | 3 |
About Yogesh Singh Rawat
Yogesh Singh Rawat is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Signal Processing, having authored 38 papers that have together received 442 indexed citations. Recurring topics across this work include Human Pose and Action Recognition (18 papers), Multimodal Machine Learning Applications (13 papers) and Anomaly Detection Techniques and Applications (12 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (292 citations), Artificial Intelligence (173 citations) and Cognitive Neuroscience (62 citations). Yogesh Singh Rawat has collaborated with scholars based in United States, Singapore and India. Frequent co-authors include Mubarak Shah, Mohan Kankanhalli, Concetto Spampinato, Akash Kumar, Mamshad Nayeem Rizve, Vibhav Vineet, Shruti Vyas, Mingli Song, Ishan R. Dave and Hamid Palangi. Their work appears in journals such as ACM Computing Surveys, IEEE Transactions on Circuits and Systems for Video Technology and IEEE Transactions on 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.