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 …

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 …

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 …

In recent years, various deep neural networks with different learning paradigms have been
widely employed in various applications, including medical diagnosis, image analysis, self …

Activation functions play a crucial role in neural networks because they are the
nonlinearities which have been attributed to the success story of deep learning. One of the …

Abstract In Convolutional Neural Networks (CNNs), the selection and use of appropriate
activation functions is of critical importance. It has been seen that the Rectified Linear Unit …

Activation functions are essential components in any neural network model; they play a
crucial role in determining the network's expressive power through their introduced non …

The choice of activation functions in Convolutional Neural Networks (CNNs) is very
important. Rectified Linear Unit (ReLU) has been widely-used in most CNNs. Recently, a …

The choice of activation functions is crucial for modern deep neural networks. Popular hand-
designed activation functions like Rectified Linear Unit (ReLU) and its variants show …

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 …