Kick: Shift-N-Overlap Cascades of Transposed Convolutional Layer for Better Autoencoding Reconstruction on Remote Sensing Imagery
A convolutional autoencoder is an essential deep neural model architecture for understanding and predicting large-scale and widespread multi-dimensional information such as remote sensing imagery. To training a convolutional autoencoder, an automatic image reconstruction from input data and evaluati...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2020-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9110496/ |