TAI-SARNET: Deep Transferred Atrous-Inception CNN for Small Samples SAR ATR

Since Synthetic Aperture Radar (SAR) targets are full of coherent speckle noise, the traditional deep learning models are difficult to effectively extract key features of the targets and share high computational complexity. To solve the problem, an effective lightweight Convolutional Neural Network...

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Detalles Bibliográficos
Autores principales: Ying, Zilu, Xuan, Chen, Zhai, Yikui, Sun, Bing, Li, Jingwen, Deng, Wenbo, Mai, Chaoyun, Wang, Faguan, Labati, Ruggero Donida, Piuri, Vincenzo, Scotti, Fabio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7146637/
https://www.ncbi.nlm.nih.gov/pubmed/32204506
http://dx.doi.org/10.3390/s20061724

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7146637/
https://www.ncbi.nlm.nih.gov/pubmed/32204506
http://dx.doi.org/10.3390/s20061724

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