Lightweight Semantic Segmentation for Fermentation Foam Monitoring: A Comparative Study of U-Net, DeepLabV3+, Fast-SCNN, and SegNet

This study aims to identify an effective neural network architecture for the task of semantic segmentation of the surface of beer wort at the stage of primary fermentation, using deep learning methodologies. Four contemporary architectures were evaluated and contrasted. The following networks are pr...

Descripció completa

Dades bibliogràfiques

Autors principals:	Maksym Vihuro, Andriy Malyar, Grzegorz Litawa, Kamila Kluczewska-Chmielarz, Tatiana Konrad, Piotr Migo
Format:	Artigo
Idioma:	Inglês
Publicat:	MDPI AG 2026-02-01
Col·lecció:	Applied Sciences
Matèries:	semantic segmentation beer deep learning U-Net Fast-SCNN DeepLabV3+
Accés en línia:	https://www.mdpi.com/2076-3417/16/3/1487
Etiquetes:	Afegir etiqueta Sense etiquetes, Sigues el primer a etiquetar aquest registre!