Adverserial Attack - Fool the Cat Grass Classifier Using Carlini and Wagner Attack

This project based on the cat-grass classifier developed using the Gaussian linear model. This project exploits possible vulnerabilities in the linear classifier, which can also apply to the deep neural network, and can be attacked easily if the parameters are known. At the end we are able to input a perturbed image that is visually identical to the input image but the output result is mostly grass.

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