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...
| Publié dans: | 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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| Auteur principal: | |
| Autres auteurs: | , , |
| Format: | Article en ligne |
| Langue: | English |
| Publié: |
2021
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| Accès à la collection: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society |
| Sujets: | Journal Article |
| Accès en ligne |
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