SWAG: A Novel Neural Network Architecture Leveraging Polynomial Activation Functions for Enhanced Deep Learning Efficiency-Reference-Cited by-同舟云学术

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SWAG: A Novel Neural Network Architecture Leveraging Polynomial Activation Functions for Enhanced Deep Learning Efficiency

Published:2024 Issue: Volume:12 Page:73363-73375
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Safaei Saeid¹^ORCID,Woods Zerotti²^ORCID,Rasheed Khaled¹,Taha Thiab R.¹,Safaei Vahid³,Gutiérrez Juan B.⁴^ORCID,Arabnia Hamid R.¹^ORCID

Affiliation:

1. Department of Computer Science, University of Georgia, Athens, GA, USA

2. Applied Physics Laboratory, Johns Hopkins University, Baltimore, MD, USA

3. Department of Mechanical Engineering, University of Isfahan, Isfahan, Iran

4. Department of Mathematics, The University of Texas at San Antonio, San Antonio, TX, USA

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6287639/10380310/10535176.pdf?arnumber=10535176

Reference41 articles.

1. Deep learning

2. Deep neural network using trainable activation functions

3. cACP-DeepGram: Classification of anticancer peptides via deep neural network and skip-gram-based word embedding model

4. iHBP-DeepPSSM: Identifying hormone binding proteins using PsePSSM based evolutionary features and deep learning approach

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