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A storage-efficient ensemble classification using filter sharing on binarized convolutional neural networks
This paper proposes a storage-efficient ensemble classification to overcome the low inference accuracy of binary neural networks (BNNs). When external power is enough in a dynamic powered system, classification results can be enhanced by aggregating outputs of multiple BNN classifiers. However, memo...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
PeerJ Inc.
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9044348/ https://www.ncbi.nlm.nih.gov/pubmed/35494815 http://dx.doi.org/10.7717/peerj-cs.924 |