Deep learning researchers have a keen interest in proposing new novel activation functions that can boost neural network performance. A good choice of activation function can have a …
An activation function is a crucial component of a neural network that introduces non- linearity in the network. The state-of-the-art performance of a neural network depends also …
Y Liu, J Zhang, C Gao, J Qu, L Ji - 2019 IEEE 5th International …, 2019 - ieeexplore.ieee.org
Activation functions playa key role in providing remarkable performance in deep neural networks, and the rectified linear unit (ReLU) is one of the most widely used activation …
Y Bai - SHS Web of Conferences, 2022 - shs-conferences.org
The activation function plays an important role in training and improving performance in deep neural networks (dnn). The rectified linear unit (relu) function provides the necessary …
C Banerjee, T Mukherjee, E Pasiliao Jr - Proceedings of the 2019 ACM …, 2019 - dl.acm.org
Deep Neural Networks have become the tool of choice for Machine Learning practitioners today. They have been successfully applied for solving a large class of learning problems …
Activation functions are essential for deep learning methods to learn and perform complex tasks such as image classification. Rectified Linear Unit (ReLU) has been widely used and …
G Madhu, S Kautish, KA Alnowibet, HM Zawbaa… - Axioms, 2023 - mdpi.com
In recent years, various deep neural networks with different learning paradigms have been widely employed in various applications, including medical diagnosis, image analysis, self …
Rectified linear activation units are important components for state-of-the-art deep convolutional networks. In this paper, we propose a novel S-shaped rectifiedlinear activation …
T Szandała - Bio-inspired neurocomputing, 2021 - Springer
The primary neural networks' decision-making units are activation functions. Moreover, they evaluate the output of networks neural node; thus, they are essential for the performance of …