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About Zhou Learning Deep Features CVPR 2016 Paper PDF
This document discusses a technique called class activation mapping (CAM) that allows convolutional neural networks trained for image classification to also localize discriminative regions within images. The key insight is that global average pooling builds a generic localizable representation by exposing the implicit attention of CNNs. Experiments show CAM can localize objects with 37.1% top-5 error on ILSVRC 2014 without bounding box supervision during training. CAM generates heatmaps highlighting important regions and can transfer this localization ability to other tasks.
Detailed Information
| Author: | ['ricksant2003'] |
|---|---|
| Publication Year: | 2020 |
| Pages: | 9 |
| Language: | English |
| Format: | |
| Price: | FREE |
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