Deep Learning using Rectified Linear Units

Abstract

We present a simple comparison of using the rectified linear units (ReLU) activation function, and a number of its variations, in a deep neural network. We present empirical results comparing ReLU functions with Logistic and Hyperbolic Tangent functions in image classification, text classification, and image reconstruction.

License

Copyright 2018-2020 Abien Fred Agarap

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
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   http://www.apache.org/licenses/LICENSE-2.0

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