28 citations · 48 across the 11 of their papers we have counts for
5 papers · 1 filter
Semi-Supervised Semantic Segmentation with Cross Teacher Training
Hui Xiao, Li Dong, Kangkang Song +4
Convolutional neural networks can achieve remarkable performance in semantic segmentation tasks. However, such neural network approaches heavily rely on costly pixel-level annotati…
Adversarial Privacy Protection on Speech Enhancement
Mingyu Dong, Diqun Yan, Rangding Wang
Speech is easily leaked imperceptibly, such as being recorded by mobile phones in different situations. Private content in speech may be maliciously extracted through speech enhanc…
Detecting and Recovering Adversarial Examples from Extracting Non-robust and Highly Predictive Adversarial Perturbations
Mingyu Dong, Jiahao Chen, Diqun Yan +3
Deep neural networks (DNNs) have been shown to be vulnerable against adversarial examples (AEs) which are maliciously designed to fool target models. The normal examples (NEs) adde…
Transferability of Adversarial Attacks on Synthetic Speech Detection
Jiacheng Deng, Shunyi Chen, Li Dong +2
Synthetic speech detection is one of the most important research problems in audio security. Meanwhile, deep neural networks are vulnerable to adversarial attacks. Therefore, we es…
Residual-Guided Non-Intrusive Speech Quality Assessment
Zhe Ye, Jiahao Chen, Diqun Yan
This paper proposes an approach to improve Non-Intrusive speech quality assessment(NI-SQA) based on the residuals between impaired speech and enhanced speech. The difficulty in our…