18 citations · 36 across the 8 of their papers we have counts for
8 papers
Gradient based Severity Labeling for Biomarker Classification in OCT
Kiran Kokilepersaud, Mohit Prabhushankar, Ghassan AlRegib +2
In this paper, we propose a novel selection strategy for contrastive learning for medical images. On natural images, contrastive learning uses augmentations to select positive and…
Learning Trajectory-Conditioned Relations to Predict Pedestrian Crossing Behavior
Chen Zhou, Ghassan AlRegib, Armin Parchami +1
In smart transportation, intelligent systems avoid potential collisions by predicting the intent of traffic agents, especially pedestrians. Pedestrian intent, defined as future act…
Forgetful Active Learning with Switch Events: Efficient Sampling for Out-of-Distribution Data
Ryan Benkert, Mohit Prabhushankar, Ghassan AlRegib
This paper considers deep out-of-distribution active learning. In practice, fully trained neural networks interact randomly with out-of-distribution (OOD) inputs and map aberrant s…
Explainable Machine Learning for Hydrocarbon Prospect Risking
Ahmad Mustafa, Ghassan AlRegib
Hydrocarbon prospect risking is a critical application in geophysics predicting well outcomes from a variety of data including geological, geophysical, and other information modali…
On the Ramifications of Human Label Uncertainty
Chen Zhou, Mohit Prabhushankar, Ghassan AlRegib
Humans exhibit disagreement during data labeling. We term this disagreement as human label uncertainty. In this work, we study the ramifications of human label uncertainty (HLU). O…
Clinical Contrastive Learning for Biomarker Detection
Kiran Kokilepersaud, Mohit Prabhushankar, Ghassan AlRegib
This paper presents a novel positive and negative set selection strategy for contrastive learning of medical images based on labels that can be extracted from clinical data. In the…
OLIVES Dataset: Ophthalmic Labels for Investigating Visual Eye Semantics
Mohit Prabhushankar, Kiran Kokilepersaud, Yash-yee Logan +3
Clinical diagnosis of the eye is performed over multifarious data modalities including scalar clinical labels, vectorized biomarkers, two-dimensional fundus images, and three-dimen…
Introspective Learning : A Two-Stage Approach for Inference in Neural Networks
Mohit Prabhushankar, Ghassan AlRegib
In this paper, we advocate for two stages in a neural network's decision making process. The first is the existing feed-forward inference framework where patterns in given data are…