Towards characterizing adversarial defects of deep learning software from the lens of uncertainty

Over the past decade, deep learning (DL) has been successfully applied to many industrial domain-specific tasks. However, the current state-of-the-art DL software still suffers from quality issues, which raises great concern especially in the context of safety- and security-critical scenarios. Adver...

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Main Authors: ZHANG, Xiyue, XIE, Xiaofei, MA, Lei, DU, Xiaoning, HU, Qiang, LIU, Yang, ZHAO, Jianjun, SUN, Meng
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2020
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Online Access:https://ink.library.smu.edu.sg/sis_research/7084
https://ink.library.smu.edu.sg/context/sis_research/article/8087/viewcontent/3377811.3380368.pdf
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Institution: Singapore Management University
Language: English
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