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 …
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 …
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 …
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 …
M Zhu, W Min, Q Wang, S Zou, X Chen - Neurocomputing, 2021 - Elsevier
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 …
Y Zhou, Z Zhu, Z Zhong - Proceedings of the IEEE/CVF …, 2021 - openaccess.thecvf.com
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 …
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 …