Developing Novel Robust Loss Functions-Based Classification Layers for DLLSTM Neural Networks-Reference-Cited by-同舟云学术

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Developing Novel Robust Loss Functions-Based Classification Layers for DLLSTM Neural Networks

Published:2023 Issue: Volume:11 Page:49863-49873
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Houran Mohamad Abou¹^ORCID,Essai Ali Mohamed H.²^ORCID,Abdel-Raman Adel B.³,Badry Eman A.⁴^ORCID,Hassan Alaaeldien¹^ORCID,Atallah Hany A.³^ORCID

Affiliation:

1. School of Electrical Engineering, Xi’an Jiaotong University, Xi’an, China

2. Department of Electrical Engineering, Faculty of Engineering, Al-Azhar University, Qena, Egypt

3. Electrical Engineering Department, Faculty of Engineering, South Valley University, Qena, Egypt

4. Department of Electrical and Communication Engineering, Higher Institute of Engineering and Technology at Al-Tod, Luxor, Egypt

Funder

National Natural Science Foundation of China

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/ielx7/6287639/10005208/10124197.pdf?arnumber=10124197

Reference43 articles.

1. Machine-Learning Methods on Noisy and Sparse Data

2. Gaussian error linear units (GELUs);hendrycks;arXiv 1606 08415,2016

3. Machine-Learning Methods for Computational Science and Engineering

4. A case for the self-adaptation of activation functions in FFANNs

5. Targeted style transfer using cycle consistent generative adversarial networks with quantitative analysis of different loss functions1

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