Detecting Adversarial Image Examples in Deep Neural Networks with Adaptive Noise Reduction
Detecting Adversarial Image Examples in Deep Neural Networks with Adaptive Noise Reduction is a scholarly work, published in 2021 in ''IEEE Transactions on Dependable and Secure Computing''. The main subjects of the publication include adversarial machine learning, anomaly detection, and digital forensics. The authors propose a straightforward method for detecting adversarial image examples, which can be directly deployed into unmodified off-the-shelf DNN models.