Target Recognition in SAR Images by Deep Learning with Training Data Augmentation

Mass production of high-quality synthetic SAR training imagery is essential for boosting the performance of deep-learning (DL)-based SAR automatic target recognition (ATR) algorithms in an open-world environment. To address this problem, we exploit both the widely used Moving and Stationary Target A...

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Detalles Bibliográficos
Autores principales: Geng, Zhe, Xu, Ying, Wang, Bei-Ning, Yu, Xiang, Zhu, Dai-Yin, Zhang, Gong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9863010/
https://www.ncbi.nlm.nih.gov/pubmed/36679740
http://dx.doi.org/10.3390/s23020941

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9863010/
https://www.ncbi.nlm.nih.gov/pubmed/36679740
http://dx.doi.org/10.3390/s23020941

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