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

Author(s): ORCID
ORCID



Medium: journal article
Language(s): English
Published in: Frattura ed Integrità Strutturale, , n. 63, v. 17
Page(s): 234-245
DOI: 10.3221/igf-esis.63.18
Abstract:

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 cannot make the full text of this publication available at this time. The full text can be accessed through the publisher via the DOI: 10.3221/igf-esis.63.18.
  • About this
    data sheet
  • Reference-ID
    10715845
  • Published on:
    21/03/2023
  • Last updated on:
    21/03/2023
 
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