SAR Target Detection Based on Domain Adaptive Faster R-CNN with Small Training Data Size
It is expensive and time-consuming to obtain a large number of labeled synthetic aperture radar (SAR) images. In the task of small training data size, the results of target detection on SAR images using deep network approaches are usually not ideal. In this study, considering that optical remote sen...
Guardado en:
Autores principales: | Yuchen Guo, Lan Du, Guoxin Lyu |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
MDPI AG
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/a2d43a04c2464102b59bff6fd4256444 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Adversarial Attack for SAR Target Recognition Based on UNet-Generative Adversarial Network
por: Chuan Du, et al.
Publicado: (2021) -
First Results on Wake Detection in SAR Images by Deep Learning
por: Roberto Del Prete, et al.
Publicado: (2021) -
Efficient Generation of Artificial Training DB for Ship Detection Using Satellite SAR Images
por: Seung-Jae Lee, et al.
Publicado: (2021) -
A Flexible Region of Interest Extraction Algorithm with Adaptive Threshold for 3-D Synthetic Aperture Radar Images
por: Liang Li, et al.
Publicado: (2021) -
L-Band SAR Co-Polarized Phase Difference Modeling for Corn Fields
por: Matías Ernesto Barber, et al.
Publicado: (2021)