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Interpreting black-box models: a review on explainable artificial intelligence
Recent years have seen a tremendous growth in Artificial Intelligence (AI)-based
methodological development in a broad range of domains. In this rapidly evolving field …
methodological development in a broad range of domains. In this rapidly evolving field …
A survey on adversarial attacks and defences
Deep learning has evolved as a strong and efficient framework that can be applied to a
broad spectrum of complex learning problems which were difficult to solve using the …
broad spectrum of complex learning problems which were difficult to solve using the …
Interpreting adversarial examples in deep learning: A review
Deep learning technology is increasingly being applied in safety-critical scenarios but has
recently been found to be susceptible to imperceptible adversarial perturbations. This raises …
recently been found to be susceptible to imperceptible adversarial perturbations. This raises …
Adversarial weight perturbation helps robust generalization
The study on improving the robustness of deep neural networks against adversarial
examples grows rapidly in recent years. Among them, adversarial training is the most …
examples grows rapidly in recent years. Among them, adversarial training is the most …
Deep learning for brain age estimation: A systematic review
Abstract Over the years, Machine Learning models have been successfully employed on
neuroimaging data for accurately predicting brain age. Deviations from the healthy brain …
neuroimaging data for accurately predicting brain age. Deviations from the healthy brain …
Adversarial attacks and defences: A survey
Deep learning has emerged as a strong and efficient framework that can be applied to a
broad spectrum of complex learning problems which were difficult to solve using the …
broad spectrum of complex learning problems which were difficult to solve using the …
Wild patterns: Ten years after the rise of adversarial machine learning
Deep neural networks and machine-learning algorithms are pervasively used in several
applications, ranging from computer vision to computer security. In most of these …
applications, ranging from computer vision to computer security. In most of these …
Threat of adversarial attacks on deep learning in computer vision: A survey
Deep learning is at the heart of the current rise of artificial intelligence. In the field of
computer vision, it has become the workhorse for applications ranging from self-driving cars …
computer vision, it has become the workhorse for applications ranging from self-driving cars …
[HTML][HTML] Review of artificial intelligence adversarial attack and defense technologies
S Qiu, Q Liu, S Zhou, C Wu - Applied Sciences, 2019 - mdpi.com
In recent years, artificial intelligence technologies have been widely used in computer
vision, natural language processing, automatic driving, and other fields. However, artificial …
vision, natural language processing, automatic driving, and other fields. However, artificial …
Why do adversarial attacks transfer? explaining transferability of evasion and poisoning attacks
Transferability captures the ability of an attack against a machine-learning model to be
effective against a different, potentially unknown, model. Empirical evidence for …
effective against a different, potentially unknown, model. Empirical evidence for …