198 citations · 311 across the 11 of their papers we have counts for
3 papers · 1 filter
Towards Imperceptible Query-limited Adversarial Attacks with Perceptual Feature Fidelity Loss
Pengrui Quan, Ruiming Guo, Mani Srivastava
Recently, there has been a large amount of work towards fooling deep-learning-based classifiers, particularly for images, via adversarial inputs that are visually similar to the be…
NeuroMask: Explaining Predictions of Deep Neural Networks through Mask Learning
Moustafa Alzantot, Amy Widdicombe, Simon Julier +1
Deep Neural Networks (DNNs) deliver state-of-the-art performance in many image recognition and understanding applications. However, despite their outstanding performance, these mod…
Binarized Convolutional Neural Networks with Separable Filters for Efficient Hardware Acceleration
Jeng-Hau Lin, Tianwei Xing, Ritchie Zhao +4
State-of-the-art convolutional neural networks are enormously costly in both compute and memory, demanding massively parallel GPUs for execution. Such networks strain the computati…