| Video abstraction: A systematic review and classification BT Truong, S Venkatesh ACM transactions on multimedia computing, communications, and applications …, 2007 | 1030 | 2007 |
| Activity recognition and abnormality detection with the switching hidden semi-markov model TV Duong, HH Bui, DQ Phung, S Venkatesh 2005 IEEE Computer Society Conference on Computer Vision and Pattern …, 2005 | 740 | 2005 |
| Nations within a nation: variations in epidemiological transition across the states of India, 1990–2016 in the Global Burden of Disease Study L Dandona, R Dandona, GA Kumar, DK Shukla, VK Paul, K Balakrishnan, ... The Lancet 390 (10111), 2437-2460, 2017 | 638 | 2017 |
| Memorizing normality to detect anomaly: Memory-augmented deep autoencoder for unsupervised anomaly detection D Gong, L Liu, V Le, B Saha, MR Mansour, S Venkatesh, A Hengel Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 526 | 2019 |
| Learning and detecting activities from movement trajectories using the hierarchical hidden Markov model NT Nguyen, DQ Phung, S Venkatesh, H Bui 2005 IEEE Computer Society Conference on Computer Vision and Pattern …, 2005 | 474 | 2005 |
| Guidelines for developing and reporting machine learning predictive models in biomedical research: a multidisciplinary view W Luo, D Phung, T Tran, S Gupta, S Rana, C Karmakar, A Shilton, ... Journal of medical Internet research 18 (12), e5870, 2016 | 426 | 2016 |
| Policy recognition in the abstract hidden markov model HH Bui, S Venkatesh, G West Journal of Artificial Intelligence Research 17, 451-499, 2002 | 389 | 2002 |
| Predicting healthcare trajectories from medical records: A deep learning approach T Pham, T Tran, D Phung, S Venkatesh Journal of biomedical informatics 69, 218-229, 2017 | 337 | 2017 |
| Fast cross-validation algorithms for least squares support vector machine and kernel ridge regression S An, W Liu, S Venkatesh Pattern Recognition 40 (8), 2154-2162, 2007 | 319 | 2007 |
| : A Convolutional Net for Medical Records P Nguyen, T Tran, N Wickramasinghe, S Venkatesh IEEE journal of biomedical and health informatics 21 (1), 22-30, 2016 | 311 | 2016 |
| Joint learning and dictionary construction for pattern recognition DS Pham, S Venkatesh 2008 IEEE conference on computer vision and pattern recognition, 1-8, 2008 | 289 | 2008 |
| Deepcare: A deep dynamic memory model for predictive medicine T Pham, T Tran, D Phung, S Venkatesh Pacific-Asia conference on knowledge discovery and data mining, 30-41, 2016 | 281 | 2016 |
| Robot navigation inspired by principles of insect vision MV Srinivasan, JS Chahl, K Weber, S Venkatesh, MG Nagle, SW Zhang Robotics and Autonomous Systems 26 (2-3), 203-216, 1999 | 266 | 1999 |
| How honeybees make grazing landings on flat surfaces MV Srinivasan, SW Zhang, JS Chahl, E Barth, S Venkatesh Biological cybernetics 83 (3), 171-183, 2000 | 263 | 2000 |
| Face recognition using kernel ridge regression S An, W Liu, S Venkatesh 2007 IEEE Conference on Computer Vision and Pattern Recognition, 1-7, 2007 | 246 | 2007 |
| New enhancements to cut, fade, and dissolve detection processes in video segmentation BT Truong, C Dorai, S Venkatesh Proceedings of the eighth ACM international conference on Multimedia, 219-227, 2000 | 206 | 2000 |
| Affective and content analysis of online depression communities T Nguyen, D Phung, B Dao, S Venkatesh, M Berk IEEE Transactions on Affective Computing 5 (3), 217-226, 2014 | 204 | 2014 |
| Outbreak investigation of Nipah virus disease in Kerala, India, 2018 G Arunkumar, R Chandni, DT Mourya, SK Singh, R Sadanandan, ... The Journal of infectious diseases 219 (12), 1867-1878, 2019 | 181 | 2019 |
| Using multiple windows to track concept drift MM Lazarescu, S Venkatesh, HH Bui Intelligent data analysis 8 (1), 29-59, 2004 | 172 | 2004 |
| GraphDTA: Predicting drug–target binding affinity with graph neural networks T Nguyen, H Le, TP Quinn, T Nguyen, TD Le, S Venkatesh Bioinformatics 37 (8), 1140-1147, 2021 | 170* | 2021 |
