Sambuddha Ghosal
Sambuddha Ghosal
Verified email at mit.edu
Title
Cited by
Cited by
Year
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
1082018
An unsupervised spatiotemporal graphical modeling approach to anomaly detection in distributed cps
C Liu, S Ghosal, Z Jiang, S Sarkar
2016 ACM/IEEE 7th International Conference on Cyber-Physical Systems (ICCPS …, 2016
332016
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
322018
An unsupervised anomaly detection approach using energy-based spatiotemporal graphical modeling
C Liu, S Ghosal, Z Jiang, S Sarkar
Cyber-physical systems 3 (1-4), 66-102, 2017
292017
A weakly supervised deep learning framework for sorghum head detection and counting
S Ghosal, B Zheng, SC Chapman, AB Potgieter, DR Jordan, X Wang, ...
Plant Phenomics 2019, 1525874, 2019
192019
Detection and analysis of combustion instability from hi-speed flame images using dynamic mode decomposition
S Ghosal, V Ramanan, S Sarkar, SR Chakravarthy, S Sarkar
ASME 2016 Dynamic Systems and Control Conference, 2016
102016
Encoding Invariances in Deep Generative Models
V Shah, A Joshi, S Ghosal, B Pokuri, S Sarkar, B Ganapathysubramanian, ...
https://arxiv.org/abs/1906.01626, 2019
42019
An unsupervised spatiotemporal graphical modeling approach to anomaly detection in distributed cps. In 2016 ACM/IEEE 7th International Conference on Cyber-Physical Systems …
C Liu, S Ghosal, Z Jiang, S Sarkar
IEEE, 2016
42016
Interpretable deep learning applied to plant stress phenotyping
S Ghosal, D Blystone, AK Singh, B Ganapathysubramanian, A Singh, ...
arXiv preprint arXiv:1710.08619, 2017
32017
High Speed Video-based health monitoring using 3D deep learning
S Ghosal, A Akintayo, P Boor, S Sarkar
Dynamic Data-Driven Application Systems (DDDAS), 2017
32017
Engineering analytics through explainable deep learning
S Ghosal
32017
Interpretable deep learning for guided microstructure-property explorations in photovoltaics
BSS Pokuri, S Ghosal, A Kokate, S Sarkar, B Ganapathysubramanian
npj Computational Materials 5 (1), 1-11, 2019
22019
An Automated Soybean Multi-Stress Detection framework using Deep Convolutional Neural Networks
S Ghosal, D Blystone, H Saha, D Mueller, B Ganapathysubramanian, ...
2*
Interpretable deep learning for guided structure-property explorations in photovoltaics
BSS Pokuri, S Ghosal, A Kokate, B Ganapathysubramanian, S Sarkar
arXiv preprint arXiv:1811.06067, 2018
12018
Data-driven persistent monitoring of Indoor Air Systems
S Ghosal, C Liu, U Passe, S He, S Sarkar
12016
Deep Generative Models Strike Back! Improving Understanding and Evaluation in Light of Unmet Expectations for OoD Data
J Just, S Ghosal
arXiv preprint arXiv:1911.04699, 2019
2019
Physics-constrained deterministic solution of time-dependent partial differential equations using deep convolutional encoder-decoders
S Ghosal
2019
Deep learning for human engineered systems: Weak supervision, interpretability and knowledge embedding
S Ghosal
2019
Research Article A Weakly Supervised Deep Learning Framework for Sorghum Head Detection and Counting
S Ghosal, B Zheng, SC Chapman, AB Potgieter, DR Jordan, X Wang, ...
2019
Binary 2D Morphologies of Polymer Phase Separation: Dataset and Python Toolbox
V Shah, A Joshi, BSS Pokuri, S Ghosal, S Sarkar, ...
2019
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