activity
20182026
most citedOLIVES Dataset: Ophthalmic Labels for Investigating Visual Eye Semantics

18 citations · 41 across the 25 of their papers we have counts for

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27 papers · 1 filter

cs.CV2026

RADMI: Latent Information Aggregation as a Proxy for Model Uncertainty

William Stevens, Mohit Prabhushankar, Ghassan AlRegib

Epistemic uncertainty estimation is essential for identifying regions where deep learning system outputs may be unreliable. However, existing approaches require computationally exp…

cs.CV2026

Information Router for Mitigating Modality Dominance in Vision-Language Models

Seulgi Kim, Mohit Prabhushankar, Ghassan AlRegib

Vision Language models (VLMs) have demonstrated strong performance across a wide range of benchmarks, yet they often suffer from modality dominance, where predictions rely dispropo…

cs.CV2026

BALD-SAM: Disagreement-based Active Prompting in Interactive Segmentation

Prithwijit Chowdhury, Mohit Prabhushankar, Ghassan AlRegib

The Segment Anything Model (SAM) has revolutionized interactive segmentation through spatial prompting. While existing work primarily focuses on automating prompts in various setti…

cs.CV2026

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…

cs.CV2025

Countering Multi-modal Representation Collapse through Rank-targeted Fusion

Seulgi Kim, Kiran Kokilepersaud, Mohit Prabhushankar +1

Multi-modal fusion methods often suffer from two types of representation collapse: feature collapse where individual dimensions lose their discriminative power (as measured by eige…

cs.CV2025

Subject Invariant Contrastive Learning for Human Activity Recognition

Yavuz Yarici, Kiran Kokilepersaud, Mohit Prabhushankar +1

The high cost of annotating data makes self-supervised approaches, such as contrastive learning methods, appealing for Human Activity Recognition (HAR). Effective contrastive learn…