Saliency Map Based Data Augmentation

• URL: http://arxiv.org/abs/2205.14686v1
• Date: Sun, 29 May 2022 15:04:59 GMT
• Title: Saliency Map Based Data Augmentation
• Authors: Jalal Al-afandi, B\'alint Magyar, Andr\'as Horv\'ath
• Abstract summary: We will present a new method which uses saliency maps to restrict the invariance of neural networks to certain regions. This method provides higher test accuracy in classification tasks.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Data augmentation is a commonly applied technique with two seemingly related advantages. With this method one can increase the size of the training set generating new samples and also increase the invariance of the network against the applied transformations. Unfortunately all images contain both relevant and irrelevant features for classification therefore this invariance has to be class specific. In this paper we will present a new method which uses saliency maps to restrict the invariance of neural networks to certain regions, providing higher test accuracy in classification tasks.

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