Embarrassingly Simple Binarization for Deep Single Imagery Super-Resolution Networks
Deep convolutional neural networks (DCCNs) have shown pleasing performance in single image super-resolution (SISR). To deploy them onto real devices with limited storage and computational resources, a promising solution is to binarize the network, i.e., quantize each float-point weight and activatio...
| Veröffentlicht in: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. - 1992. - 30(2021) vom: 22., Seite 3934-3945 |
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| Format: | Online-Aufsatz |
| Sprache: | English |
| Veröffentlicht: |
2021
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society |
| Schlagworte: | Journal Article |
| Online verfügbar |
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