Unsupervised Domain Adaptation for Image Classification and Object Detection Using Guided Transfer Learning Approach and JS Divergence

Unsupervised domain adaptation (UDA) is a transfer learning technique utilized in deep learning. UDA aims to reduce the distribution gap between labeled source and unlabeled target domains by adapting a model through fine-tuning. Typically, UDA approaches assume the same categories in both domains....

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Detalles Bibliográficos
Autores principales: Goel, Parth, Ganatra, Amit
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10181527/
https://www.ncbi.nlm.nih.gov/pubmed/37177640
http://dx.doi.org/10.3390/s23094436

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10181527/
https://www.ncbi.nlm.nih.gov/pubmed/37177640
http://dx.doi.org/10.3390/s23094436

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