Rectified Exponential Units for Convolutional Neural Networks
Rectified linear unit (ReLU) plays an important role in today's convolutional neural networks (CNNs). In this paper, we propose a novel activation function called Rectified Exponential Unit (REU). Inspired by two recently proposed activation functions: Exponential Linear Unit (ELU) and Swish, t...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2019-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/8762191/ |