Part-based approximations for morphological operators using asymmetric auto-encoders

DOI10.1007/978-3-030-20867-7_25zbMath1445.68312arXiv1904.00763OpenAlexW2930937638MaRDI QIDQ2189384

Isabelle Bloch, Jesús Angulo, Samy Blusseau, Bastien Ponchon, Santiago Velasco-Forero

Publication date: 15 June 2020

Full work available at URL: https://arxiv.org/abs/1904.00763

zbMATH Keywords

mathematical morphologyrepresentation learningauto-encodersmorphological invariancenon-negative sparse coding

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Computing methodologies for image processing (68U10) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)

Related Items (2)

Approximating morphological operators with part-based representations learned by asymmetric auto-encoders ⋮ Editorial -- special issue: ISMM 2019

This page was built for publication: Part-based approximations for morphological operators using asymmetric auto-encoders