Zobrazeno 1 - 10 of 26 pro vyhledávání: '"Yoshinao ISOBE"'
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Akademický článek
Improved Surprise Adequacy Tools for Corner Case Data Description and Detection
Autor: Tinghui Ouyang, Vicent Sanz Marco, Yoshinao Isobe, Hideki Asoh, Yutaka Oiwa, Yoshiki Seo
Publikováno v: Applied Sciences, Vol 11, Iss 15, p 6826 (2021)
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 cas
Externí odkaz: https://doaj.org/article/8881d140ae6443d19136765c71a80940
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3
AI robustness analysis with consideration of corner cases
Autor: Tinghui Ouyang, Yutaka Oiwa, Yoshiki Seo, Vicent Sanz Marco, Yoshinao Isobe, Jun Ogata
Publikováno v: AITest
Corner cases are a set of high-risk data in deep learning (DL) systems, which could lead to incorrect and unexpected behaviors. To study corner cases' influence on DL models' robustness and stability, this paper implemented a research with corner cas
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::46aea45a39901500567f2d54c02bd771
https://doi.org/10.1109/aitest52744.2021.00016
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4
Improved Surprise Adequacy Tools for Corner Case Data Description and Detection
Autor: Yutaka Oiwa, Tinghui Ouyang, Yoshinao Isobe, Vicent Sanz Marco, Hideki Asoh, Yoshiki Seo
Publikováno v: Applied Sciences, Vol 11, Iss 6826, p 6826 (2021)
Applied Sciences
Volume 11
Issue 15
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 cas
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8daaaa35fdf0418da18fb90f14da9078
https://www.mdpi.com/2076-3417/11/15/6826
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6
Corner case data description and detection
Autor: Yutaka Oiwa, Tinghui Ouyang, Hideki Asoh, Yoshinao Isobe, Yoshiki Seo, Vicent Sanz Marco
Publikováno v: WAIN@ICSE
As the major factors affecting the safety of deep learning models, corner cases and related detection are crucial in AI quality assurance for constructing safety- and security-critical systems. The generic corner case researches involve two interesti
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a2f266f6b533d58cdb90e0ffe6efedc8
http://arxiv.org/abs/2101.02494
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