Benchmarking Domain Adaptation Methods on Aerial Datasets

Deep learning grew in importance in recent years due to its versatility and excellent performance on supervised classification tasks. A core assumption for such supervised approaches is that the training and testing data are drawn from the same underlying data distribution. This may not always be th...

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Detalles Bibliográficos
Autores principales: Nagananda, Navya, Taufique, Abu Md Niamul, Madappa, Raaga, Jahan, Chowdhury Sadman, Minnehan, Breton, Rovito, Todd, Savakis, Andreas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8662429/
https://www.ncbi.nlm.nih.gov/pubmed/34884072
http://dx.doi.org/10.3390/s21238070

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8662429/
https://www.ncbi.nlm.nih.gov/pubmed/34884072
http://dx.doi.org/10.3390/s21238070

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