Roots are essential for acquiring water and nutrients to sustain and support plant growth and
anchorage. However, they have been studied less than the aboveground traits in …

State-of-the-art classical neural networks are observed to be vulnerable to small crafted
adversarial perturbations. A more severe vulnerability has been noted for quantum machine …

Robustness to adversarial attacks is typically evaluated with adversarial accuracy. While
essential, this metric does not capture all aspects of robustness and in particular leaves out …

This paper analyzes a deep learning based classification process for common East Asian
dermatological conditions. We have chosen ten common categories based on prevalence …

Existing studies have shown that malicious and imperceptible adversarial samples may
significantly weaken the reliability and validity of deep learning systems. Since gradient …

This thesis being the preliminary culmination of my academic journey, I feel it appropriate to
thank a number of people who have been a positive influence along the way. First and …

Deep convolutional neural networks have achieved great successes over recent years,
particularly in the domain of computer vision. They are fast, convenient, and–thanks to …

The existence of adversarial examples has led to considerable uncertainty regarding the
trust one can justifiably put in predictions produced by automated systems. This uncertainty …

Adversarial robustness of machine learning models has attracted considerable attention
over recent years. Adversarial attacks undermine the reliability of and trust in machine …

Adversarial examples are artificially crafted to mislead deep learning systems into making
wrong decisions. In the research of attack algorithms against multi-class image classifiers …