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of 122
pro vyhledávání: '"Dong, Mingyu"'
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) added with imperceptible adversarial perturbation, can be a security threa
Externí odkaz:
http://arxiv.org/abs/2206.15128
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 enhancement technology. Speech enhancement technology has developed rapidly
Externí odkaz:
http://arxiv.org/abs/2206.08170
Publikováno v:
In Sensors and Actuators Reports June 2024 7
Autor:
Ye, Xurui, Zhang, Mengyun, Gong, Zihao, Jiao, Weiting, Li, Liangchao, Dong, Mingyu, Xiang, Tianyu, Feng, Nianjie, Wu, Qian
Publikováno v:
In Phytomedicine June 2024 128
An automatic speech recognition (ASR) system based on a deep neural network is vulnerable to attack by an adversarial example, especially if the command-dependent ASR fails. A defense method against adversarial examples is proposed to improve the rob
Externí odkaz:
http://arxiv.org/abs/2108.13562
Publikováno v:
In Applied Energy 1 February 2024 355
Autor:
Fu, Yinxin, Liu, Lu, Zhang, Jiahan, Wang, Lan, Dong, Mingyu, McClements, David Julian, Wan, Fangyun, Shen, Peiyi, Li, Qian
Publikováno v:
In International Journal of Biological Macromolecules 31 December 2023 253 Part 3
Publikováno v:
In Computers & Industrial Engineering September 2023 183
Autor:
Li, Qian, Liu, Lu, Zhang, Jiahan, Dong, Mingyu, Wang, Lan, Julian McClements, David, Fu, Yinxin, Han, Lingyu, Shen, Peiyi, Chen, Xiaoqiang
Publikováno v:
In Food Chemistry 1 June 2023 410
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