Polarimetric synthetic aperture radar (PolSAR) images are classified mainly according to the backscattering information of ground objects. For regions with complex backscattering information, misclassification is easy to occur, which leads to challenges in improving the classification accuracy of the PolSAR image. Given this situation, this paper combines the Deep Learning Model and traditional classifiers to classify PolSAR image. First, the Convolution Neural Network (CNN) was used to classify the PolSAR image and according to the category prediction probability of pixels, the key pixels easily misclassified are located. Then, the adaptive boosting (AdaBoost) algorithm combined the three shallow classifiers (the Support Vector Machine (SV...
The integration of deep learning and active learning has achieved great success in polarimetric synt...
With various remote sensing technologies to aid Earth Observation, radar-based imaging is one of the...
The deep convolution neural network (CNN), which has prominent advantages in feature learning, can l...
Classification of polarimetric synthetic aperture radar (PolSAR) images is an active research area w...
Recently, deep neural networks have received intense interests in polarimetric synthetic aperture ra...
Classification of polarimetric synthetic aperture radar (PolSAR) images is an active research area w...
Polarimetric synthetic aperture radar (PolSAR) image classification has become more and more popular...
Polarimetric synthetic aperture radar (PolSAR) images contain useful information, which can lead to ...
Convolutional neural networks (CNN) have achieved great success in the optical image processing fiel...
Convolutional neural networks (CNN) have achieved great success in the optical image processing fiel...
The deep convolution neural network (CNN), which has prominent advantages in feature learning, can l...
Inspired by enormous success of fully convolutional network (FCN) in semantic segmentation, as well ...
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 ...
The integration of deep learning and active learning has achieved great success in polarimetric synt...
The integration of deep learning and active learning has achieved great success in polarimetric synt...
With various remote sensing technologies to aid Earth Observation, radar-based imaging is one of the...
The deep convolution neural network (CNN), which has prominent advantages in feature learning, can l...
Classification of polarimetric synthetic aperture radar (PolSAR) images is an active research area w...
Recently, deep neural networks have received intense interests in polarimetric synthetic aperture ra...
Classification of polarimetric synthetic aperture radar (PolSAR) images is an active research area w...
Polarimetric synthetic aperture radar (PolSAR) image classification has become more and more popular...
Polarimetric synthetic aperture radar (PolSAR) images contain useful information, which can lead to ...
Convolutional neural networks (CNN) have achieved great success in the optical image processing fiel...
Convolutional neural networks (CNN) have achieved great success in the optical image processing fiel...
The deep convolution neural network (CNN), which has prominent advantages in feature learning, can l...
Inspired by enormous success of fully convolutional network (FCN) in semantic segmentation, as well ...
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 ...
The integration of deep learning and active learning has achieved great success in polarimetric synt...
The integration of deep learning and active learning has achieved great success in polarimetric synt...
With various remote sensing technologies to aid Earth Observation, radar-based imaging is one of the...
The deep convolution neural network (CNN), which has prominent advantages in feature learning, can l...