19 citations · 42 across the 3 of their papers we have counts for
3 papers
cs.CV2019★ 19 cited
Fooling Detection Alone is Not Enough: First Adversarial Attack against Multiple Object Tracking
Yunhan Jia, Yantao Lu, Junjie Shen +3
Recent work in adversarial machine learning started to focus on the visual perception in autonomous driving and studied Adversarial Examples (AEs) for object detection models. Howe…
cs.LG2019★ 11 cited
Enhancing Cross-task Transferability of Adversarial Examples with Dispersion Reduction
Yunhan Jia, Yantao Lu, Senem Velipasalar +2
Neural networks are known to be vulnerable to carefully crafted adversarial examples, and these malicious samples often transfer, i.e., they maintain their effectiveness even again…
cs.LG2017★ 12 cited
Modularized Morphing of Neural Networks
Tao Wei, Changhu Wang, Chang Wen Chen
In this work we study the problem of network morphism, an effective learning scheme to morph a well-trained neural network to a new one with the network function completely preserv…