Data-driven Verification of DNNs for Object Recognition

Clemens Otte, Yinchong Yang, Danny Benlin Oswan

The paper proposes a new testing approach for Deep Neural Networks (DNN) using gradient-free optimization to find perturbation chains that successfully falsify the tested DNN, goin…