Deep learning researchers have a keen interest in proposing two new novel activation
functions which can boost network performance. A good choice of activation function can …

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 …

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 …

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 …

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 …

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 …

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 …