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On the Reduction of Computational Complexity of Deep Convolutional Neural Networks †

Deep convolutional neural networks (ConvNets), which are at the heart of many new emerging applications, achieve remarkable performance in audio and visual recognition tasks. Unfortunately, achieving accuracy often implies significant computational costs, limiting deployability. In modern ConvNets i...

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Vydáno v:Entropy (Basel)
Hlavní autoři: Maji, Partha, Mullins, Robert
Médium: Artigo
Jazyk:Inglês
Vydáno: MDPI 2018
Témata:
On-line přístup:https://ncbi.nlm.nih.gov/pmc/articles/PMC7512823/
https://ncbi.nlm.nih.gov/pubmed/33265396
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/e20040305
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