Semi-Supervised Domain Adaptation for Holistic Counting under Label Gap

This paper proposes a novel approach for semi-supervised domain adaptation for holistic regression tasks, where a DNN predicts a continuous value [Formula: see text] given an input image x. The current literature generally lacks specific domain adaptation approaches for this task, as most of them mo...

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Detalles Bibliográficos
Autores principales: Litrico, Mattia, Battiato, Sebastiano, Tsaftaris, Sotirios A., Giuffrida, Mario Valerio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8541592/
https://www.ncbi.nlm.nih.gov/pubmed/34677284
http://dx.doi.org/10.3390/jimaging7100198

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8541592/
https://www.ncbi.nlm.nih.gov/pubmed/34677284
http://dx.doi.org/10.3390/jimaging7100198

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