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Sambuddha Ghosal
Sambuddha Ghosal
Sr. Research Data Scientist @ Bayer R&D, MIT
Verified email at mit.edu - Homepage
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
5532018
NTIRE 2018 Challenge on Spectral Reconstruction from RGB Images
B Arad, O Ben-Shahar, R Timofte, LV Gool, L Zhang, MH Yang, Z Xiong, ...
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition …, 2018
2592018
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
1822019
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
682016
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), 95, 2019
612019
Deep multiview image fusion for soybean yield estimation in breeding applications
LG Riera, ME Carroll, Z Zhang, JM Shook, S Ghosal, T Gao, A Singh, ...
Plant Phenomics, 2021
512021
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
412017
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
362019
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
Dynamic Systems and Control Conference 50695, V001T12A005, 2016
212016
Uncertainty quantified deep learning for predicting dice coefficient of digital histopathology image segmentation
S Ghosal, A Xie, P Shah
arXiv preprint arXiv:2109.00115, 2021
92021
A deep-learning toolkit for visualization and interpretation of segmented medical images
S Ghosal, P Shah
Cell Reports Methods 1 (7), 2021
72021
Generative models for solving nonlinear partial differential equations
A Joshi, V Shah, S Ghosal, B Pokuri, S Sarkar, B Ganapathysubramanian, ...
Proc. of NeurIPS Workshop on ML for Physics, 2019
72019
Interpretable deep learning applied to plant stress phenotyping
S Ghosal, D Blystone, AK Singh, B Ganapathysubramanian, A Singh, ...
arXiv preprint arXiv:1710.08619, 2017
72017
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
72017
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
52018
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
42019
Interpretable and synergistic deep learning for visual explanation and statistical estimations of segmentation of disease features from medical images
S Ghosal, P Shah
arXiv preprint arXiv:2011.05791, 2020
32020
A Weakly Supervised Deep Learning Framework for Sorghum Head Detection and Counting. 2019
S Ghosal, B Zheng, SC Chapman, AB Potgieter, DR Jordan, X Wang, ...
Publisher: Science Partner 2019, 2019
32019
Binary 2D Morphologies of Polymer Phase Separation: Dataset and Python Toolbox
V Shah, A Joshi, BSS Pokuri, S Ghosal, S Sarkar, ...
Zenodo, 2019
22019
Engineering analytics through explainable deep learning
S Ghosal
Iowa State University, 2017
22017
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