Assessing the Threat of Adversarial Examples on Deep Neural Networks for Remote Sensing Scene Classification: Attacks and Defenses

Bo Du
Bo Du
Liangpei Zhang
Liangpei Zhang

IEEE Trans. Geosci. Remote. Sens., pp. 1604-1617, 2020.

Cited by: 0|Bibtex|Views4|DOI:https://doi.org/10.1109/TGRS.2020.2999962
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Other Links: academic.microsoft.com|dblp.uni-trier.de

Abstract:

Deep neural networks, which can learn the representative and discriminative features from data in a hierarchical manner, have achieved state-of-the-art performance in the remote sensing scene classification task. Despite the great success that deep learning algorithms have obtained, their vulnerability toward adversarial examples deserves...More

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