Training Convolutional Neural Networks with Multi-Size Images and Triplet Loss for Remote Sensing Scene Classification

Many remote sensing scene classification algorithms improve their classification accuracy by additional modules, which increases the parameters and computing overhead of the model at the inference stage. In this paper, we explore how to improve the classification accuracy of the model without adding...

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Detalles Bibliográficos
Autores principales: Zhang, Jianming, Lu, Chaoquan, Wang, Jin, Yue, Xiao-Guang, Lim, Se-Jung, Al-Makhadmeh, Zafer, Tolba, Amr
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7070623/
https://www.ncbi.nlm.nih.gov/pubmed/32098092
http://dx.doi.org/10.3390/s20041188

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7070623/
https://www.ncbi.nlm.nih.gov/pubmed/32098092
http://dx.doi.org/10.3390/s20041188

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