all AI news
Deep-learning-based decomposition of overlapping-sparse images: application at the vertex of neutrino interactions
May 9, 2024, 4:42 a.m. | Sa\'ul Alonso-Monsalve, Davide Sgalaberna, Xingyu Zhao, Adrien Molines, Clark McGrew, Andr\'e Rubbia
cs.LG updates on arXiv.org arxiv.org
Abstract: Image decomposition plays a crucial role in various computer vision tasks, enabling the analysis and manipulation of visual content at a fundamental level. Overlapping images, which occur when multiple objects or scenes partially occlude each other, pose unique challenges for decomposition algorithms. The task intensifies when working with sparse images, where the scarcity of meaningful information complicates the precise extraction of components. This paper presents a solution that leverages the power of deep learning to …
abstract algorithms analysis application arxiv challenges computer computer vision cs.cv cs.lg enabling fundamental hep-ex image images interactions manipulation multiple objects role tasks type unique vertex vision visual
More from arxiv.org / cs.LG updates on arXiv.org
Jobs in AI, ML, Big Data
Software Engineer for AI Training Data (School Specific)
@ G2i Inc | Remote
Software Engineer for AI Training Data (Python)
@ G2i Inc | Remote
Software Engineer for AI Training Data (Tier 2)
@ G2i Inc | Remote
Data Engineer
@ Lemon.io | Remote: Europe, LATAM, Canada, UK, Asia, Oceania
Artificial Intelligence – Bioinformatic Expert
@ University of Texas Medical Branch | Galveston, TX
Lead Developer (AI)
@ Cere Network | San Francisco, US