HcLSH: A Novel Non-Linear Monotonic Activation Function for Deep Learning Methods-Reference-Cited by-同舟云学术

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HcLSH: A Novel Non-Linear Monotonic Activation Function for Deep Learning Methods

Published:2023 Issue: Volume:11 Page:47794-47815
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Abdel-Nabi Heba¹^ORCID,Al-Naymat Ghazi²^ORCID,Ali Mostafa Z.³^ORCID,Awajan Arafat¹^ORCID

Affiliation:

1. Department of Computer Science, Princess Sumaya University for Technology, Amman, Jordan

2. Artificial Intelligence Research Center (AIRC), College of Engineering and Information Technology, Ajman University, Ajman, United Arab Emirates

3. Faculty of Computer and Information Technology, Jordan University of Science & Technology, Irbid, Jordan

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10124188.pdf?arnumber=10124188

Reference52 articles.

1. Activation functions in deep learning: A comprehensive survey and benchmark

2. An Efficient Asymmetric Nonlinear Activation Function for Deep Neural Networks

3. ReLTanh: An activation function with vanishing gradient resistance for SAE-based DNNs and its application to rotating machinery fault diagnosis

4. Efficient BackProp

5. ImageNet: A large-scale hierarchical image database

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