We use a convolutional LSTM (ConvLSTM) along with a sequence of polarization coherent matrices in rotation domain for PolSAR image classification. First, nine ...
This work uses a convolutional LSTM (ConvLSTM) along with a sequence of polarization coherent matrices in rotation domain for PolSAR image classification ...
We use a convolutional LSTM. (ConvLSTM) along with a sequence of polarization coherent matrices in rotation domain for PolSAR image classification. First, nine ...
To using rotation information of PolSAR image for improving classification performance, the authors built a convolutional LSTM (ConvLSTM) along a sequence of ...
Jan 16, 2023 · In this paper, a hybrid attention-based encoder–decoder fully convolutional network (HA-EDNet) is presented for PolSAR classification.
Classification of SAR and PolSAR images using deep learning: a review
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The general objective of the paper is to help researchers in identifying a deep learning technique appropriate for SAR or PolSAR image classification.
Learning Rotation Domain Deep Mutual Information Using Convolutional LSTM for Unsupervised PolSAR Image Classification. Language: English; Authors: Wang, Lei ...
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ConvLSTM has taken the place of LSTM's [38] fully connected gate layers with convolutional layers, enabling it to process sequence data with spatial information ...
Multi-pixel simultaneous classification of PolSAR image using convolutional neural networks ... Exploring convolutional LSTM for PolSAR image classification. L ...
Experiments on real PolSAR images show that the proposed model achieves the best classification results with an extremely low sampling rate of 0.1%.