Sanketh Shetty
Impact in
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- Human Pose and Action Recognition
- Video Surveillance and Tracking Methods
- Multimodal Machine Learning Applications
- Video Analysis and Summarization
- Advanced Neural Network Applications
- Human-Computer Interaction top 0.5%
- Hand Gesture Recognition Systems
Papers in
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- Video Surveillance and Tracking Methods 2
- Human Pose and Action Recognition 2
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- Advanced Clustering Algorithms Research 1
- Co-authors
- George Toderici (2 shared papers)Andrej Karpathy (2 shared papers)Thomas Leung (2 shared papers)Rahul Sukthankar (2 shared papers)Li Fei-Fei (2 shared papers)Zhengang Peng (1 shared paper)Laurent Marrot (1 shared paper)Steve Thomas Pannakal (2 shared papers)
- Journals
- Phytochemical Analysis (1 paper)Antioxidants (1 paper)Proceedings - International Conference on Pattern Recognition (1 paper)
- Partner nations
- FranceUnited StatesIndia
In The Last Decade
Sanketh Shetty
5 papers receiving 4.6k citations
Sanketh Shetty's Hit Papers
Peers
Comparison fields: 5 of 171
- Computer Vision and Pattern Recognition 3.7k
- Human-Computer Interaction 444
- Artificial Intelligence 2.0k
- Signal Processing 268
- Biomedical Engineering 760
Countries citing papers authored by Sanketh Shetty
This map shows the geographic impact of Sanketh Shetty'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 Sanketh Shetty with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sanketh Shetty more than expected).
Fields of papers citing papers by Sanketh Shetty
This network shows the impact of papers produced by Sanketh Shetty. 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 Sanketh Shetty. The network helps show where Sanketh Shetty may publish in the future.
Co-authors
The 16 scholars most cited alongside Sanketh Shetty, 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 | Large-Scale Video Classification with Convolutional Neural Networks Hit paper breakdown → | 2014 | 4161 |
| 2 | Large-scale Video Classification with Convolutional Neural Networks Hit paper breakdown → | 2014 | 578 |
| 3 | 2021 | 22 | |
| 4 | 2025 | 3 | |
| 5 | 2008 | 2 | |
| 6 | Primary Splenic Lymphoma: A rare clinical case report | 2011 | 0 |
About Sanketh Shetty
Sanketh Shetty is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Biochemistry, Molecular Biology and Pharmacology, having authored 6 papers that have together received 4.8k indexed citations. Recurring topics across this work include Video Surveillance and Tracking Methods (2 papers), Human Pose and Action Recognition (2 papers), Lymphoma Diagnosis and Treatment (1 paper), Bioactive natural compounds (1 paper), Chronic Lymphocytic Leukemia Research (1 paper), Advanced Clustering Algorithms Research (1 paper), Skin Protection and Aging (1 paper) and Antioxidant Activity and Oxidative Stress (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (3.7k citations), Human-Computer Interaction (444 citations), Artificial Intelligence (2.0k citations), Signal Processing (268 citations) and Biomedical Engineering (760 citations). Sanketh Shetty has collaborated with scholars based in France, United States and India. Frequent co-authors include George Toderici, Andrej Karpathy, Thomas Leung, Rahul Sukthankar, Li Fei-Fei, Zhengang Peng, Laurent Marrot, Steve Thomas Pannakal, Joan Eilstein and Narendra Ahuja. Their work appears in journals such as Phytochemical Analysis, Antioxidants and Proceedings - International Conference on Pattern Recognition.
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.