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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...

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Autores principales: Maksym Vihuro, Andriy Malyar, Grzegorz Litawa, Kamila Kluczewska-Chmielarz, Tatiana Konrad, Piotr Migo
Formato: Artigo
Lenguaje:Inglês
Publicado: MDPI AG 2026-02-01
Colección:Applied Sciences
Materias:
semantic segmentation
beer
deep learning
U-Net
Fast-SCNN
DeepLabV3+
Acceso en línea:https://www.mdpi.com/2076-3417/16/3/1487
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