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Neural Prototype Trees for Interpretable Fine-grained Image Recognition

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), (2021)

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Abstract

Interpretable machine learning addresses the black-box nature of deep neural networks. Visual prototypes have been suggested for intrinsically interpretable image recognition, instead of generating post-hoc explanations that approximate a trained model. However, a large number of prototypes can be overwhelming. To reduce explanation siz...More

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Author
Meike Nauta
Meike Nauta
Ron van Bree
Ron van Bree
Christin Seifert
Christin Seifert
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