[HTML][HTML] Polarimetric imaging via deep learning: A review
Polarization can provide information largely uncorrelated with the spectrum and intensity.
Therefore, polarimetric imaging (PI) techniques have significant advantages in many fields …
Therefore, polarimetric imaging (PI) techniques have significant advantages in many fields …
Classification of SAR and PolSAR images using deep learning: A review
Advancement in remote sensing technology and microwave sensors explores the
applications of remote sensing in different fields. Microwave remote sensing encompasses …
applications of remote sensing in different fields. Microwave remote sensing encompasses …
Complex-valued convolutional neural network and its application in polarimetric SAR image classification
Following the great success of deep convolutional neural networks (CNNs) in computer
vision, this paper proposes a complex-valued CNN (CV-CNN) specifically for synthetic …
vision, this paper proposes a complex-valued CNN (CV-CNN) specifically for synthetic …
Building extraction in very high resolution remote sensing imagery using deep learning and guided filters
Y Xu, L Wu, Z ** is an important application of remote sensing which aims at both
estimation and change in land cover under the urban area. A major challenge being faced …
estimation and change in land cover under the urban area. A major challenge being faced …
Polarimetric SAR image semantic segmentation with 3D discrete wavelet transform and Markov random field
Polarimetric synthetic aperture radar (PolSAR) image segmentation is currently of great
importance in image processing for remote sensing applications. However, it is a …
importance in image processing for remote sensing applications. However, it is a …
Dense connection and depthwise separable convolution based CNN for polarimetric SAR image classification
Convolution neural networks (CNN) have achieved great success in natural image
processing where large amounts of training data are available. However, for the polarimetric …
processing where large amounts of training data are available. However, for the polarimetric …
A graph-based semisupervised deep learning model for PolSAR image classification
Aiming at improving the classification accuracy with limited numbers of labeled pixels in
polarimetric synthetic aperture radar (PolSAR) image classification task, this paper presents …
polarimetric synthetic aperture radar (PolSAR) image classification task, this paper presents …
A lightweight complex-valued DeepLabv3+ for semantic segmentation of PolSAR image
Semantic image segmentation is one kindof end-to-end segmentation method which can
classify the target region pixel by pixel. As a classic semantic segmentation network in …
classify the target region pixel by pixel. As a classic semantic segmentation network in …
An active deep learning approach for minimally supervised PolSAR image classification
Recently, deep neural networks have received intense interests in polarimetric synthetic
aperture radar (PolSAR) image classification. However, its success is subject to the …
aperture radar (PolSAR) image classification. However, its success is subject to the …