ManiFool
Algorithm for evaluating the invariance properties of deep networks
Deep convolutional neural networks have been shown to be vulnerable to arbitrary geometric transformations. However, there is no systematic method to measure the invariance properties of deep networks to such transformations. ManiFool is a simple yet scalable algorithm to measure the invariance of deep networks. In particular, it measures the robustness of deep networks to geometric transformations in a worst-case regime as they can be problematic for sensitive applications.
inactive
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entered showcase: 2019-03-18
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entry updated: 2024-03-21
This project has not yet been evaluated by the C4DT Factory team.
We will be happy to evaluate it upon request.
Application
Python