3 citations · 5 across the 3 of their papers we have counts for
3 papers
TAP-VL: Text Layout-Aware Pre-training for Enriched Vision-Language Models
Jonathan Fhima, Elad Ben Avraham, Oren Nuriel +4
Vision-Language (VL) models have garnered considerable research interest; however, they still face challenges in effectively handling text within images. To address this limitation…
LUNet: Deep Learning for the Segmentation of Arterioles and Venules in High Resolution Fundus Images
Jonathan Fhima, Jan Van Eijgen, Hana Kulenovic +7
The retina is the only part of the human body in which blood vessels can be accessed non-invasively using imaging techniques such as digital fundus images (DFI). The spatial distri…
PVBM: A Python Vasculature Biomarker Toolbox Based On Retinal Blood Vessel Segmentation
Jonathan Fhima, Jan Van Eijgen, Ingeborg Stalmans +3
Introduction: Blood vessels can be non-invasively visualized from a digital fundus image (DFI). Several studies have shown an association between cardiovascular risk and vascular f…