Learning to Zoom: a Saliency-Based Sampling Layer for Neural Networks
© Springer Nature Switzerland AG 2018. We introduce a saliency-based distortion layer for convolutional neural networks that helps to improve the spatial sampling of input data for a given task. Our differentiable layer can be added as a preprocessing block to existing task networks and trained alto...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Springer International Publishing,
2021-11-09T12:18:19Z.
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| Subjects: | |
| Online Access: | Get fulltext |