Cats Are Not Fish: Deep Learning Testing Calls for Out-Of-Distribution Awareness

As Deep Learning (DL) is continuously adopted in many industrial applications, its quality and reliability start to raise concerns. Similar to the traditional software development process, testing the DL software to uncover its defects at an early stage is an effective way to reduce risks after depl...

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Veröffentlicht in:	2020 35th IEEE/ACM International Conference on Automated Software Engineering (ASE) S. 1041 - 1052
Hauptverfasser:	Berend, David, Xie, Xiaofei, Ma, Lei, Zhou, Lingjun, Liu, Yang, Xu, Chi, Zhao, Jianjun
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	ACM 01.09.2020
Schlagworte:	Data models Deep learning Deep learning testing out of distribution quality assurance Software Software engineering Software reliability Testing Training data
ISSN:	2643-1572
Online-Zugang:	Volltext
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