Efficient compression of encoder-decoder models for semantic segmentation using the separation index

Abstract We present a novel approach to compressing encoder–decoder architectures, particularly in semantic segmentation tasks, by leveraging the Separation Index (SI)—a metric that quantifies how distinctly a network’s feature maps separate different classes at the pixel level. By identifying and p...

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Detalles Bibliográficos

Autores principales:	Movahed Jamshidi, Ahmad Kalhor, Abdol-Hossein Vahabie
Formato:	Artigo
Lenguaje:	Inglês
Publicado:	Nature Portfolio 2025-07-01
Colección:	Scientific Reports
Materias:	Model compression Encoder-Decoder architectures Semantic segmentation Separation index
Acceso en línea:	https://doi.org/10.1038/s41598-025-10348-9
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