Block-Wise Separable Convolutions: An Alternative Way to Factorize Standard Convolutions

Block-Wise Separable Convolutions: An Alternative Way to Factorize Standard Convolutions

In this paper, we introduce block-wise separable convolutions (BlkSConv) to replace the standard convolutions for compressing deep CNN models. First, BlkSConv expresses the standard convolutional kernel as an ordered set of block vectors each of which is a linear combination of fixed basis block vec...

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Bibliographic Details
Main Authors:	Yan-Jen Huang, Hsin-Lung Wu, Ching-Chen
Format:	Article
Language:	English
Published:	IEEE 2024-01-01
Series:	IEEE Access
Subjects:	Convolutional neural network block-wise separable convolution network architecture search
Online Access:	https://ieeexplore.ieee.org/document/10414068/

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