An efficient semi-sigmoidal non-linear activation function approach for deep neural networks

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An efficient semi-sigmoidal non-linear activation function approach for deep neural networks

A non-linear activation function is one of the key contributing factors to the success of Deep Learning (DL). Since the revival of DL takes place in 2012, Rectified Linear Unit (ReLU) has been regarded as a de facto standard for many DL models by the community. Despite its popularity, however, Re...

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Bibliographic Details
Main Author:	Chieng, Hock Hung
Format:	Thesis
Language:	English English English
Published:	2022
Subjects:	QA76 Computer software
Online Access:	http://eprints.uthm.edu.my/8409/ http://eprints.uthm.edu.my/8409/1/24p%20CHIENG%20HOCK%20HUNG.pdf http://eprints.uthm.edu.my/8409/2/CHIENG%20HOCK%20HUNG%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/8409/3/CHIENG%20HOCK%20HUNG%20WATERMARK.pdf

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