| Machine learning for high-throughput stress phenotyping in plants A Singh, B Ganapathysubramanian, AK Singh, S Sarkar Trends in plant science 21 (2), 110-124, 2016 | 297 | 2016 |
| LLNet: A deep autoencoder approach to natural low-light image enhancement KG Lore, A Akintayo, S Sarkar Pattern Recognition 61, 650-662, 2017 | 205 | 2017 |
| Review and comparative evaluation of symbolic dynamic filtering for detection of anomaly patterns C Rao, A Ray, S Sarkar, M Yasar Signal, Image and Video Processing 3 (2), 101-114, 2009 | 134 | 2009 |
| An explainable deep machine vision framework for plant stress phenotyping S Ghosal, D Blystone, AK Singh, B Ganapathysubramanian, A Singh, ... Proceedings of the National Academy of Sciences 115 (18), 4613-4618, 2018 | 110 | 2018 |
| Deep learning for plant stress phenotyping: trends and future perspectives AK Singh, B Ganapathysubramanian, S Sarkar, A Singh Trends in plant science 23 (10), 883-898, 2018 | 87 | 2018 |
| Data-driven fault detection in aircraft engines with noisy sensor measurements S Sarkar, X Jin, A Ray Journal of Engineering for Gas Turbines and Power 133 (8), 2011 | 73 | 2011 |
| Fault detection and isolation in aircraft gas turbine engines. Part 1: Underlying concept S Gupta, A Ray, S Sarkar, M Yasar Proceedings of the Institution of Mechanical Engineers, Part G: Journal of …, 2008 | 59 | 2008 |
| A real-time phenotyping framework using machine learning for plant stress severity rating in soybean HS Naik, J Zhang, A Lofquist, T Assefa, S Sarkar, D Ackerman, A Singh, ... Plant methods 13 (1), 23, 2017 | 56 | 2017 |
| Collaborative deep learning in fixed topology networks Z Jiang, A Balu, C Hegde, S Sarkar Advances in Neural Information Processing Systems, 5904-5914, 2017 | 52 | 2017 |
| Fault detection and isolation in aircraft gas turbine engines. Part 2: validation on a simulation test bed S Sarkar, M Yasar, S Gupta, A Ray, K Mukherjee Proceedings of the Institution of Mechanical Engineers, Part G: Journal of …, 2008 | 45 | 2008 |
| Computer vision and machine learning for robust phenotyping in genome-wide studies J Zhang, HS Naik, T Assefa, S Sarkar, RVC Reddy, A Singh, ... Scientific Reports 7 (1), 1-11, 2017 | 40 | 2017 |
| Sensor fusion for fault detection and classification in distributed physical processes S Sarkar, S Sarkar, N Virani, A Ray, M Yasar Frontiers in Robotics and AI 1, 16, 2014 | 37 | 2014 |
| Anomaly detection in nuclear power plants via symbolic dynamic filtering X Jin, Y Guo, S Sarkar, A Ray, RM Edwards IEEE Transactions on Nuclear Science 58 (1), 277-288, 2010 | 36 | 2010 |
| Generalization of Hilbert transform for symbolic analysis of noisy signals S Sarkar, K Mukherjee, A Ray Signal Processing 89 (6), 1245-1251, 2009 | 36 | 2009 |
| An adaptive spatiotemporal feature learning approach for fault diagnosis in complex systems T Han, C Liu, L Wu, S Sarkar, D Jiang Mechanical Systems and Signal Processing 117, 170-187, 2019 | 35 | 2019 |
| Prognostics of combustion instabilities from hi-speed flame video using a deep convolutional selective autoencoder A Akintayo, KG Lore, S Sarkar, S Sarkar International Journal of Prognostics and Health Management 7 (023), 1-14, 2016 | 35* | 2016 |
| Multivariate exploration of non-intrusive load monitoring via spatiotemporal pattern network C Liu, A Akintayo, Z Jiang, GP Henze, S Sarkar Applied energy 211, 1106-1122, 2018 | 34 | 2018 |
| Multi-sensor information fusion for fault detection in aircraft gas turbine engines S Sarkar, S Sarkar, K Mukherjee, A Ray, A Srivastav Proceedings of the Institution of Mechanical Engineers, Part G: Journal of …, 2013 | 33 | 2013 |
| Ntire 2018 challenge on spectral reconstruction from rgb images B Arad, O Ben-Shahar, R Timofte Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 32 | 2018 |
| Deep learning for automated occlusion edge detection in RGB-D frames S Sarkar, V Venugopalan, K Reddy, J Ryde, N Jaitly, M Giering Journal of Signal Processing Systems 88 (2), 205-217, 2017 | 32* | 2017 |
Asok RayDistinguished Professor of Mechanical Engineering and MathematicsVerified email at psu.edu
