154 citations · 491 across the 25 of their papers we have counts for
5 papers · 1 filter
AdvKnn: Adversarial Attacks On K-Nearest Neighbor Classifiers With Approximate Gradients
Xiaodan Li, Yuefeng Chen, Yuan He +1
Deep neural networks have been shown to be vulnerable to adversarial examples---maliciously crafted examples that can trigger the target model to misbehave by adding imperceptible…
Learning To Characterize Adversarial Subspaces
Xiaofeng Mao, Yuefeng Chen, Yuhong Li +2
Deep Neural Networks (DNNs) are known to be vulnerable to the maliciously generated adversarial examples. To detect these adversarial examples, previous methods use artificially de…
Self-supervised Adversarial Training
Kejiang Chen, Hang Zhou, Yuefeng Chen +6
Recent work has demonstrated that neural networks are vulnerable to adversarial examples. To escape from the predicament, many works try to harden the model in various ways, in whi…
Self-Supervised Learning For Few-Shot Image Classification
Da Chen, Yuefeng Chen, Yuhong Li +3
Few-shot image classification aims to classify unseen classes with limited labelled samples. Recent works benefit from the meta-learning process with episodic tasks and can fast ad…
Bilinear Representation for Language-based Image Editing Using Conditional Generative Adversarial Networks
Xiaofeng Mao, Yuefeng Chen, Yuhong Li +3
The task of Language-Based Image Editing (LBIE) aims at generating a target image by editing the source image based on the given language description. The main challenge of LBIE is…