74 citations · 173 across the 30 of their papers we have counts for
35 papers
Predicting Ki67, ER, PR, and HER2 Statuses from H&E-stained Breast Cancer Images
Amir Akbarnejad, Nilanjan Ray, Penny J. Barnes +1
Despite the advances in machine learning and digital pathology, it is not yet clear if machine learning methods can accurately predict molecular information merely from histomorpho…
Training-based Model Refinement and Representation Disagreement for Semi-Supervised Object Detection
Seyed Mojtaba Marvasti-Zadeh, Nilanjan Ray, Nadir Erbilgin
Semi-supervised object detection (SSOD) aims to improve the performance and generalization of existing object detectors by utilizing limited labeled data and extensive unlabeled da…
Document Image Cleaning using Budget-Aware Black-Box Approximation
Ganesh Tata, Katyani Singh, Eric Van Oeveren +1
Recent work has shown that by approximating the behaviour of a non-differentiable black-box function using a neural network, the black-box can be integrated into a differentiable t…
Towards Early Prediction of Human iPSC Reprogramming Success
Abhineet Singh, Ila Jasra, Omar Mouhammed +3
This paper presents advancements in automated early-stage prediction of the success of reprogramming human induced pluripotent stem cells (iPSCs) as a potential source for regenera…
Weakly Supervised Realtime Dynamic Background Subtraction
Fateme Bahri, Nilanjan Ray
Background subtraction is a fundamental task in computer vision with numerous real-world applications, ranging from object tracking to video surveillance. Dynamic backgrounds poses…
Crown-CAM: Interpretable Visual Explanations for Tree Crown Detection in Aerial Images
Seyed Mojtaba Marvasti-Zadeh, Devin Goodsman, Nilanjan Ray +1
Visual explanation of ``black-box'' models allows researchers in explainable artificial intelligence (XAI) to interpret the model's decisions in a human-understandable manner. In t…