Three Decades of Activations: A Comprehensive Survey of 400 Activation Functions for Neural Networks

V Kunc, J Kléma - arXiv preprint arXiv:2402.09092, 2024 - arxiv.org
Neural networks have proven to be a highly effective tool for solving complex problems in
many areas of life. Recently, their importance and practical usability have further been …

PolyLU: A simple and robust polynomial-based linear unit activation function for deep learning

HS Feng, CH Yang - IEEE Access, 2023 - ieeexplore.ieee.org
The activation function has a critical influence on whether a convolutional neural network in
deep learning can converge or not; a proper activation function not only makes the …

Image-based identification of optical quality and functional properties in inkjet-printed electronics using machine learning

M Polomoshnov, KM Reichert, L Rettenberger… - Journal of Intelligent …, 2024 - Springer
We propose a novel image-analysis based machine-learning approach to the fully-
automated identification of the optical quality, of functional properties, and of manufacturing …

[PDF][PDF] Conditional random k satisfiability modeling for k= 1, 2 (CRAN2SAT) with non-monotonic Smish activation function in discrete Hopfield neural network

N Roslan, S Sathasivam, FL Azizan - AIMS Mathematics, 2024 - aimspress.com
Conditional random k satisfiability modeling for k =1,2 (CRAN2SAT) with non-monotonic Smish
activation function in discrete Hopf Page 1 AIMS Mathematics, 9(2): 3911–3956. DOI …

Automated Novel Heterogeneous Meditation Tradition Classification via Optimized Chi-Squared 1DCNN Method

A Jain, R Raja - Journal of Information Technology Management, 2023 - jitm.ut.ac.ir
The realm of human-computer interaction delves deep into understanding how individuals
acquire knowledge and integrate technology into their everyday lives. Among the various …