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Very high resolution images are promising for detecting change regions and identifying change patterns. However, the low overall separability makes it difficult to discriminate change features. In this paper, a framework is proposed to simultaneously detect change regions and identify change patterns. A supervised approach is illustrated within this framework, which is aimed at reducing the overlaps...
An automatic change detection method based on conditional random field (CRF) is presented for high resolution remote sensing images in this paper. Marginalized denoising autoencoder is used to generate the difference image. The clustering results of Fuzzy C-means are applied to initialize the unary potentials of CRF. A scaled squared Euclidean distance between neighboring pixels in the observed images...
In this paper, a novel change detection method learned from Recurrent Neural Network with transferable ability is proposed. The proposed method, which is based on an improved Long Short Term Memory (LSTM) model, aims at: 1) learning a novel change detection rule to distinguish changed regions with high accuracy; 2) analyzing a new target data with transferable ability from learned change rule; 3)...
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