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- This Looks Like That: Deep Learning for Interpretable Image Recognition
When we are faced with challenging image classification tasks, we often explain our reasoning by dissecting the image, and pointing out prototypical aspects of one class or another The mounting evidence for each of the classes helps us make our final decision
- This looks like that | Proceedings of the 33rd International Conference . . .
Our experiments show that ProtoPNet can achieve comparable accuracy with its analogous non-interpretable counterpart, and when several ProtoPNets are combined into a larger network, it can achieve an accuracy that is on par with some of the best-performing deep models
- This looks like that: deep learning for interpretable image recognition . . .
In this work, we introduce a deep network architecture that reasons in a similar way: the network dissects the image by finding prototypical parts, and combines evidence from the prototypes to make a final classification
- This Looks Like That: Deep Learning for Interpretable Image Recognition
When we are faced with challenging image classification tasks, we often explain our reasoning by dissecting the image, and pointing out prototypical aspects of one class or another
- ProtoPNet this_looks_like_that. pdf at master - GitHub
This code package implements the prototypical part network (ProtoPNet) from the paper "This Looks Like That: Deep Learning for Interpretable Image Recognition" (to appear at NeurIPS 2019), by Chaofan Chen* (Duke University), Oscar Li* (Duke University), Chaofan Tao (Duke University), Alina Jade Barnett (Duke University), Jonathan Su (MIT
- Deep learning - Wikipedia
For example, in image recognition, they might learn to identify images that contain cats by analyzing example images that have been manually labeled as "cat" or "no cat" and using the analytic results to identify cats in other images
- This Looks Like That: Deep Learning for Interpretable Image Recognition
The model is able to identify several parts of the image where it thinks that this identified part of the image looks like that prototypical part of some training image, and makes its prediction based on a weighted combination of the similarity scores
- What Is Deep Learning? Neural Networks, Applications Tools
Explore the fundamentals of deep learning, from neural networks and deep neural architectures to real-world applications like AI writing, detection, vision, and more Learn how deep learning powers modern AI and which tools to use in 2025
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