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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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| Published in: | Advanced Intelligent Systems |
|---|---|
| Format: | Online Article RSS Article |
| Published: |
2026
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| _version_ | 1870116638048649216 |
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| collection | WordPress RSS FRELIP Feed Integration |
| container_title | Advanced Intelligent Systems |
| description | |
| discipline_display | Artificial Intelligence |
| discipline_facet | Artificial Intelligence |
| format | Online Article RSS Article |
| genre | Journal Article |
| id | rss_article:100875 |
| institution | FRELIP |
| journal_source_facet | Advanced Intelligent Systems |
| last_indexed | 2026-07-08T03:43:26.021Z |
| publishDate | 2026 |
| publishDateSort | 2026 |
| record_format | rss_article |
| spellingShingle | Deep Learning Approaches for Classifying Crack States With Overload and Predicting Fatigue Parameters in a Titanium Alloy Artificial Intelligence General Artificial Intelligence |
| sub_discipline_display | General |
| sub_discipline_facet | General |
| subject_display | Artificial Intelligence General Artificial Intelligence |
| subject_facet | Artificial Intelligence General Artificial Intelligence |
| title | Deep Learning Approaches for Classifying Crack States With Overload and Predicting Fatigue Parameters in a Titanium Alloy |
| title_alt | Enfoques de aprendizaje profundo para clasificar estados de grieta con sobrecarga y predecir parámetros de fatiga en una aleación de titanio Approches d'apprentissage profond pour classer les états de fissure avec surcharge et prédire les paramètres de fatigue dans un alliage de titane Abordagens de Aprendizado Profundo para Classificar Estados de Trinca com Sobrecarga e Predizer Parâmetros de Fadiga em uma Liga de Titânio |
| title_auth | Deep Learning Approaches for Classifying Crack States With Overload and Predicting Fatigue Parameters in a Titanium Alloy |
| title_es_txt | Enfoques de aprendizaje profundo para clasificar estados de grieta con sobrecarga y predecir parámetros de fatiga en una aleación de titanio |
| title_fr_txt | Approches d'apprentissage profond pour classer les états de fissure avec surcharge et prédire les paramètres de fatigue dans un alliage de titane |
| title_full | Deep Learning Approaches for Classifying Crack States With Overload and Predicting Fatigue Parameters in a Titanium Alloy |
| title_fullStr | Deep Learning Approaches for Classifying Crack States With Overload and Predicting Fatigue Parameters in a Titanium Alloy |
| title_full_unstemmed | Deep Learning Approaches for Classifying Crack States With Overload and Predicting Fatigue Parameters in a Titanium Alloy |
| title_pt_txt | Abordagens de Aprendizado Profundo para Classificar Estados de Trinca com Sobrecarga e Predizer Parâmetros de Fadiga em uma Liga de Titânio |
| title_short | Deep Learning Approaches for Classifying Crack States With Overload and Predicting Fatigue Parameters in a Titanium Alloy |
| title_sort | deep learning approaches for classifying crack states with overload and predicting fatigue parameters in a titanium alloy |
| topic | Artificial Intelligence General Artificial Intelligence |
| url | https://advanced.onlinelibrary.wiley.com/doi/10.1002/aisy.202501059?af=R |