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Computer Vision Algorithm for the detection of fracture cracks in Oil Hardening Non-Shrinking (OHNS) die steel after machining process

Auteur(s): ORCID
ORCID



Médium: article de revue
Langue(s): anglais
Publié dans: Frattura ed Integrità Strutturale, , n. 63, v. 17
Page(s): 234-245
DOI: 10.3221/igf-esis.63.18
Abstrait:

A variant of neural network for processing with images is a convolutional neural network (CNN). This type of neural network receives input from an image and extracts features from the image while also providing learnable parameters to effectively do the classification, detection, and many other tasks. In the present work, U-Net convolutional neural network is implemented on Jupyter platform by using Python programming for fracture surface image segmentation in Oil Hardening Non-Shrinking (OHNS) die steel after the machining process. The results showed that the fracture cracks can be validated by testing with higher accuracy.

Structurae ne peut pas vous offrir cette publication en texte intégral pour l'instant. Le texte intégral est accessible chez l'éditeur. DOI: 10.3221/igf-esis.63.18.
  • Informations
    sur cette fiche
  • Reference-ID
    10715845
  • Publié(e) le:
    21.03.2023
  • Modifié(e) le:
    21.03.2023
 
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