A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf
.
Change Detection in SAR Images using Deep Belief Network: a New Training Approach based on Morphological Images
2019
IET Image Processing
In solving change detection problem, unsupervised methods are usually preferred to their supervised counterparts due to the difficulty of producing labelled data. Nevertheless, in this paper, a supervised deep learning-based method is presented for change detection in synthetic aperture radar (SAR) images. A Deep Belief Network (DBN) was employed as the deep architecture in the proposed method, and the training process of this network included unsupervised feature learning followed by
doi:10.1049/iet-ipr.2018.6248
fatcat:bql3vqzm5rbhplpxaglbicfsyq