Jaime Laviada, Guillermo Álvarez-Narciandi, Fernando Las-Heras

Some novel methods for imaging based on synthetic aperture radar can result in images contaminated by artifacts as a consequence of pushing the limits of the algorithms. In order to mitigate the impact of this artifacts, image translation techniques can be exploited enabling to turn the SAR image into a cleaner one. For this purpose, multiple techniques can be used such as convolutional neural networks or generative adversial networks. However, the training of those systems can require a high number of images, which can be computationally expensive to generate.

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[1] Jaime Laviada, Guillermo Álvarez-Narciandi, Fernando Las-Heras, "Synthetic aperture radar images for cGAN training", IEEE Dataport, 2022. [Online]. Available: http://dx.doi.org/10.21227/5gzt-cm67. Accessed: Dec. 26, 2024.
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url = {http://dx.doi.org/10.21227/5gzt-cm67},
author = {Jaime Laviada; Guillermo Álvarez-Narciandi; Fernando Las-Heras },
publisher = {IEEE Dataport},
title = {Synthetic aperture radar images for cGAN training},
year = {2022} }
TY - DATA
T1 - Synthetic aperture radar images for cGAN training
AU - Jaime Laviada; Guillermo Álvarez-Narciandi; Fernando Las-Heras
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Jaime Laviada, Guillermo Álvarez-Narciandi, Fernando Las-Heras. (2022). Synthetic aperture radar images for cGAN training. IEEE Dataport. http://dx.doi.org/10.21227/5gzt-cm67
Jaime Laviada, Guillermo Álvarez-Narciandi, Fernando Las-Heras, 2022. Synthetic aperture radar images for cGAN training. Available at: http://dx.doi.org/10.21227/5gzt-cm67.
Jaime Laviada, Guillermo Álvarez-Narciandi, Fernando Las-Heras. (2022). "Synthetic aperture radar images for cGAN training." Web.
1. Jaime Laviada, Guillermo Álvarez-Narciandi, Fernando Las-Heras. Synthetic aperture radar images for cGAN training [Internet]. IEEE Dataport; 2022. Available from : http://dx.doi.org/10.21227/5gzt-cm67
Jaime Laviada, Guillermo Álvarez-Narciandi, Fernando Las-Heras. "Synthetic aperture radar images for cGAN training." doi: 10.21227/5gzt-cm67