Vikash Sehwag

52 total papers · 652 total citations
4 papers, 31 citations indexed

Vikash Sehwag is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing. According to data from OpenAlex, Vikash Sehwag has authored 4 papers receiving a total of 31 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Artificial Intelligence, 2 papers in Computer Vision and Pattern Recognition and 1 paper in Signal Processing. Recurrent topics in Vikash Sehwag’s work include Anomaly Detection Techniques and Applications (2 papers), Adversarial Robustness in Machine Learning (2 papers) and Domain Adaptation and Few-Shot Learning (1 paper). Vikash Sehwag is often cited by papers focused on Anomaly Detection Techniques and Applications (2 papers), Adversarial Robustness in Machine Learning (2 papers) and Domain Adaptation and Few-Shot Learning (1 paper). Vikash Sehwag collaborates with scholars based in United States. Vikash Sehwag's co-authors include Prateek Mittal, Mung Chiang, Cristian Canton Ferrer, Caner Hazırbaş, Albert Gordo, Arjun Nitin Bhagoji and Chong Xiang and has published in prestigious journals such as SHILAP Revista de lepidopterología, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) and USENIX Security Symposium.