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Deep Learning Approaches for Classifying Crack States With Overload and Predicting Fatigue Parameters in a Titanium Alloy.

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Title: Deep Learning Approaches for Classifying Crack States With Overload and Predicting Fatigue Parameters in a Titanium Alloy.
Authors: Choi, Seon Du1, Timilsina, Suman2, Shin, Youn Woo1, Kwon, Yong Nam1, kyn1740@kims.re.kr, Sohn, Kee‐Sun3, kssohn@sejong.ac.kr, Kim, Ji Sik4, jisikkim@knu.ac.kr
Source: Advanced Intelligent Systems (2640-4567); Jun2026, Vol. 8 Issue 6, p1-15, 15p
Database: Applied Science & Technology Source
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Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 195039340
AccessLevel: 2
PubType: Academic Journal
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        Value: 10.1002/aisy.202501059
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      – Code: eng
        Text: English
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        PageCount: 15
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      – TitleFull: Deep Learning Approaches for Classifying Crack States With Overload and Predicting Fatigue Parameters in a Titanium Alloy.
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            NameFull: Choi, Seon Du
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            NameFull: Timilsina, Suman
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            NameFull: Shin, Youn Woo
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            NameFull: Kwon, Yong Nam
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            – D: 01
              M: 06
              Text: Jun2026
              Type: published
              Y: 2026
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