Memory‐ and time‐efficient dense network for single‐image super‐resolution
Abstract Dense connections in convolutional neural networks (CNNs), which connect each layer to every other layer, can compensate for mid/high‐frequency information loss and further enhance high‐frequency signals. However, dense CNNs suffer from high memory usage due to the accumulation of concatena...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2021-04-01
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| Series: | IET Signal Processing |
| Online Access: | https://doi.org/10.1049/sil2.12020 |