15 citations · 48 across the 19 of their papers we have counts for
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cs.CV2022★ 7 cited
Foiling Explanations in Deep Neural Networks
Snir Vitrack Tamam, Raz Lapid, Moshe Sipper
Deep neural networks (DNNs) have greatly impacted numerous fields over the past decade. Yet despite exhibiting superb performance over many problems, their black-box nature still p…
cs.CV2022★ 13 cited
An Evolutionary, Gradient-Free, Query-Efficient, Black-Box Algorithm for Generating Adversarial Instances in Deep Networks
Raz Lapid, Zvika Haramaty, Moshe Sipper
Deep neural networks (DNNs) are sensitive to adversarial data in a variety of scenarios, including the black-box scenario, where the attacker is only allowed to query the trained m…
cs.NE2022★ 15 cited
Evolution of Activation Functions for Deep Learning-Based Image Classification
Raz Lapid, Moshe Sipper
Activation functions (AFs) play a pivotal role in the performance of neural networks. The Rectified Linear Unit (ReLU) is currently the most commonly used AF. Several replacements…