QR Code

Overlap-aware segmentation for topological reconstruction of obscured objects

The separation of overlapping objects presents a significant challenge in scientific imaging. While deep learning segmentation-regression algorithms can predict pixel-wise intensities, they typically treat all regions equally rather than prioritizing overlap regions where attribution is most ambiguo...

Description complète

Enregistré dans:
Auteurs principaux: J Schueler, H M Araújo, S N Balashov, J E Borg, C Brew, F M Brunbauer, C Cazzaniga, A Cottle, D Edgeman, C D Frost, F Garcia, D Hunt, M Kastriotou, P Knights, H Kraus, A Lindote, M Lisowska, D Loomba, E Lopez Asamar, P A Majewski, T Marley, C McCabe, L Millins, R Nandakumar, T Neep, F Neves, K Nikolopoulos, E Oliveri, A Roy, Timothy J Sumner, E Tilly, W Thompson, M A Vogiatzi
Format: Artigo
Langue:Inglês
Publié: IOP Publishing 2026-01-01
Collection:Machine Learning: Science and Technology
Sujets:
segmentation-regression
deep learning
scientific imaging
dark matter
MIGDAL
Accès en ligne:https://doi.org/10.1088/2632-2153/ae6e18
Tags: Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires