KANB: A Family of Parametric Activation Functions With Trainable Parameters

In this paper, a new family of four-parameter activation functions, referred to as KANB, is introduced to improve the performance of artificial neural networks (ANNs). The activation functions have been designed and tested under various problem settings –covering various ANN architectures...

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Bibliographic Details

Published in:	IEEE Access
Main Authors:	George Kanakoudis, Petros Mandalis, Nikolaos Pelekis
Format:	Article
Language:	English
Published:	IEEE 2025-01-01
Subjects:	Adaptive activation function trainable parameters trainable activation function deep learning
Online Access:	https://ieeexplore.ieee.org/document/11129700/