2PFPCE: Two-Phase Filter Pruning Based on Conditional Entropy

Deep Convolutional Neural Networks~(CNNs) offer remarkable performance of classifications and regressions in many high-dimensional problems and have been widely utilized in real-word cognitive applications. However, high computational cost of CNNs greatly hinder their deployment in resource-constrai...

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Veröffentlicht in:	arXiv.org 2018-09
Hauptverfasser:	Min, Chuhan, Wang, Aosen, Chen, Yiran, Xu, Wenyao, Chen, Xin
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Artificial neural networks Compression ratio Computing time Edge computing Entropy Inference Neural networks Optimization Performance degradation Pruning Reduction
Online-Zugang:	Volltext
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