FPWT: Filter pruning via wavelet transform for CNNs

The enormous data and computational resources required by Convolutional Neural Networks (CNNs) hinder the practical application on mobile devices. To solve this restrictive problem, filter pruning has become one of the practical approaches. At present, most existing pruning methods are currently dev...

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Veröffentlicht in:	Neural networks 2024-11, Vol.179, p.106577, Article 106577
Hauptverfasser:	Liu, Yajun, Fan, Kefeng, Zhou, Wenju
Format:	Artikel
Sprache:	eng
Schlagworte:	Energy-weighted coefficients Feature map Filter pruning Wavelet transform
Online-Zugang:	Volltext
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