Deep Learning Toolbox Verification Library
Verify and test robustness of deep learning networks
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Mise à jour
11 sept. 2024
Deep Learning Toolbox Verification Library enables testing robustness properties of deep learning networks.
Use this library to:
- Verify network robustness to adversarial examples (Since R2022b)
- Estimate how sensitive the network predictions are to input perturbation (Since R2022b)
- Explain object detection network predictions using D-RISE (Since R2024a)
- Create a distribution discriminator that separates data into in- and out-of-distribution (Since R2023a)
- Detect out-of-distribution (ODD) data in neural networks (Since R2023a)
- Generate C/C++ and CUDA code for out-of-distribution (runtime monitoring) (Since R2023a)
Please refer to the documentation here: https://www.mathworks.com/help/deeplearning/verification.html
If you have download or installation problems, please contact Technical Support: https://www.mathworks.com/support/contact_us.html
Compatibilité avec les versions de MATLAB
Créé avec
R2022b
Compatible avec les versions R2022b à R2024b
Plateformes compatibles
Windows macOS (Apple Silicon) macOS (Intel) LinuxTags
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