Revisiting Consistency for Semi-Supervised Semantic Segmentation †

Semi-supervised learning is an attractive technique in practical deployments of deep models since it relaxes the dependence on labeled data. It is especially important in the scope of dense prediction because pixel-level annotation requires substantial effort. This paper considers semi-supervised al...

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Detalles Bibliográficos
Autores principales: Grubišić, Ivan, Oršić, Marin, Šegvić, Siniša
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9865240/
https://www.ncbi.nlm.nih.gov/pubmed/36679735
http://dx.doi.org/10.3390/s23020940

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9865240/
https://www.ncbi.nlm.nih.gov/pubmed/36679735
http://dx.doi.org/10.3390/s23020940

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