On the Reduction of Computational Complexity of Deep Convolutional Neural Networks

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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Bibliographic Details
Main Authors: Partha Maji, Robert Mullins
Format: Article
Language:English
Published: MDPI AG 2018-04-01
Series:Entropy
Subjects:
convolutional neural network
deep learning
computational optimization
hardware implementation
Online Access:http://www.mdpi.com/1099-4300/20/4/305

Internet

http://www.mdpi.com/1099-4300/20/4/305

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