most citedPropagated Perturbation of Adversarial Attack for well-known CNNs: Empirical Study and its Explanation

2 citations · 2 across the 2 of their papers we have counts for

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2 papers

cs.CV2019★ 2 cited

Propagated Perturbation of Adversarial Attack for well-known CNNs: Empirical Study and its Explanation

Jihyeun Yoon, Kyungyul Kim, Jongseong Jang

Deep Neural Network based classifiers are known to be vulnerable to perturbations of inputs constructed by an adversarial attack to force misclassification. Most studies have focus…

cs.CV2019

Bin-wise Temperature Scaling (BTS): Improvement in Confidence Calibration Performance through Simple Scaling Techniques

Byeongmoon Ji, Hyemin Jung, Jihyeun Yoon +2

The prediction reliability of neural networks is important in many applications. Specifically, in safety-critical domains, such as cancer prediction or autonomous driving, a reliab…