Polarimetric synthetic aperture radar (PolSAR) image classification is a pixel-wise issue, which has become increasingly prevalent in recent years. As a variant of the Convolutional Neural Network (CNN), the Fully Convolutional Network (FCN), which is designed for pixel-to-pixel tasks, has obtained enormous success in semantic segmentation. Therefore, effectively using the FCN model combined with polarimetric characteristics for PolSAR image classification is quite promising. This paper proposes a novel FCN model by adopting complex-valued domain stacked-dilated convolution (CV-SDFCN). Firstly, a stacked-dilated convolution layer with different dilation rates is constructed to capture multi-scale features of PolSAR image; meanwhile, the sha...
A polarimetric synthetic aperture radar (PolSAR) sensor is able to collect images in different polar...
A polarimetric synthetic aperture radar (PolSAR) sensor is able to collect images in different polar...
Despite the state-of-the-art performance of the deep learning methods for Synthetic Aperture Radar (...
Polarimetric synthetic aperture radar (PolSAR) image classification has become more and more popular...
Convolutional neural networks (CNN) have achieved great success in the optical image processing fiel...
Inspired by enormous success of fully convolutional network (FCN) in semantic segmentation, as well ...
Polarimetric synthetic aperture radar (PolSAR) image classification has become more and more widely ...
Polarimetric synthetic aperture radar (PolSAR) images contain useful information, which can lead to ...
Classification of polarimetric synthetic aperture radar (PolSAR) images is an active research area w...
Fully polarimetric synthetic aperture radar (PolSAR) can transmit and receive electromagnetic energy...
Deep learning has successfully improved the classification accuracy of optical remote sensing images...
Deep learning has successfully improved the classification accuracy of optical remote sensing images...
The deep convolution neural network (CNN), which has prominent advantages in feature learning, can l...
International audienceIn this work, we exploit convolutional neural networks (CNNs) for the classifi...
Recently, deep learning models, such as autoencoder, deep belief network and convolutional autoencod...
A polarimetric synthetic aperture radar (PolSAR) sensor is able to collect images in different polar...
A polarimetric synthetic aperture radar (PolSAR) sensor is able to collect images in different polar...
Despite the state-of-the-art performance of the deep learning methods for Synthetic Aperture Radar (...
Polarimetric synthetic aperture radar (PolSAR) image classification has become more and more popular...
Convolutional neural networks (CNN) have achieved great success in the optical image processing fiel...
Inspired by enormous success of fully convolutional network (FCN) in semantic segmentation, as well ...
Polarimetric synthetic aperture radar (PolSAR) image classification has become more and more widely ...
Polarimetric synthetic aperture radar (PolSAR) images contain useful information, which can lead to ...
Classification of polarimetric synthetic aperture radar (PolSAR) images is an active research area w...
Fully polarimetric synthetic aperture radar (PolSAR) can transmit and receive electromagnetic energy...
Deep learning has successfully improved the classification accuracy of optical remote sensing images...
Deep learning has successfully improved the classification accuracy of optical remote sensing images...
The deep convolution neural network (CNN), which has prominent advantages in feature learning, can l...
International audienceIn this work, we exploit convolutional neural networks (CNNs) for the classifi...
Recently, deep learning models, such as autoencoder, deep belief network and convolutional autoencod...
A polarimetric synthetic aperture radar (PolSAR) sensor is able to collect images in different polar...
A polarimetric synthetic aperture radar (PolSAR) sensor is able to collect images in different polar...
Despite the state-of-the-art performance of the deep learning methods for Synthetic Aperture Radar (...