Improved Surprise Adequacy Tools for Corner Case Data Description and Detection

Improved Surprise Adequacy Tools for Corner Case Data Description and Detection

Facing the increasing quantity of AI models applications, especially in life- and property-related fields, it is crucial for designers to construct safety- and security-critical systems. As a major factor affecting the safety of AI models, corner case data and its related description/detection techn...

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Bibliographic Details
Main Authors: Tinghui Ouyang, Vicent Sanz Marco, Yoshinao Isobe, Hideki Asoh, Yutaka Oiwa, Yoshiki Seo
Format: Article
Language:English
Published: MDPI AG 2021-07-01
Series:Applied Sciences
Subjects:
corner case data detection
surprise adequacy
modified distanced-based SA
AI quality testing
Online Access:https://www.mdpi.com/2076-3417/11/15/6826

Internet

https://www.mdpi.com/2076-3417/11/15/6826

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