78 citations · 121 across the 9 of their papers we have counts for
9 papers
Deep Learning with Uncertainty Quantification for Predicting the Segmentation Dice Coefficient of Prostate Cancer Biopsy Images
Audrey Xie, Elhoucine Elfatimi, Sambuddha Ghosal +1
Deep learning models (DLMs) can achieve state-of-the-art performance in histopathology image segmentation and classification, but have limited deployment potential in real-world cl…
Deep Multi-view Image Fusion for Soybean Yield Estimation in Breeding Applications Deep Multi-view Image Fusion for Soybean Yield Estimation in Breeding Applications
Luis G Riera, Matthew E. Carroll, Zhisheng Zhang +8
Reliable seed yield estimation is an indispensable step in plant breeding programs geared towards cultivar development in major row crops. The objective of this study is to develop…
Interpretable and synergistic deep learning for visual explanation and statistical estimations of segmentation of disease features from medical images
Sambuddha Ghosal, Pratik Shah
Deep learning (DL) models for disease classification or segmentation from medical images are increasingly trained using transfer learning (TL) from unrelated natural world images.…
Deep Generative Models Strike Back! Improving Understanding and Evaluation in Light of Unmet Expectations for OoD Data
John Just, Sambuddha Ghosal
Advances in deep generative and density models have shown impressive capacity to model complex probability density functions in lower-dimensional space. Also, applying such models…
Encoding Invariances in Deep Generative Models
Viraj Shah, Ameya Joshi, Sambuddha Ghosal +4
Reliable training of generative adversarial networks (GANs) typically require massive datasets in order to model complicated distributions. However, in several applications, traini…
Anomalous diffusion in an electrolyte saturated paper matrix
Sankha Shuvra Das, Sumeet Kumar, Sambuddha Ghosal +2
Diffusion of colored dye on water saturated paper substrates has been traditionally exploited with great skill by renowned water color artists. The same physics finds more recent p…
Interpretable deep learning for guided structure-property explorations in photovoltaics
Balaji Sesha Sarath Pokuri, Sambuddha Ghosal, Apurva Kokate +2
The performance of an organic photovoltaic device is intricately connected to its active layer morphology. This connection between the active layer and device performance is very e…
Interpretable Deep Learning applied to Plant Stress Phenotyping
Sambuddha Ghosal, David Blystone, Asheesh K. Singh +3
Availability of an explainable deep learning model that can be applied to practical real world scenarios and in turn, can consistently, rapidly and accurately identify specific and…
An unsupervised spatiotemporal graphical modeling approach to anomaly detection in distributed CPS
Chao Liu, Sambuddha Ghosal, Zhanhong Jiang +1
Modern distributed cyber-physical systems (CPSs) encounter a large variety of physical faults and cyber anomalies and in many cases, they are vulnerable to catastrophic fault propa…