Deep learning-supported machine vision-based hybrid system combining inhomogeneous 2D and 3D data for the identification of surface defects-Reference-Cited by-同舟云学术

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Deep learning-supported machine vision-based hybrid system combining inhomogeneous 2D and 3D data for the identification of surface defects

Published:2024-07-12 Issue:1 Volume:12 Page:
ISSN:2169-3277
Container-title:Production & Manufacturing Research
language:en
Short-container-title:Production & Manufacturing Research

Author:

Cavaliere Giorgio¹²,Lanz Oswald¹³,Borgianni Yuri¹,Savio Enrico⁴

Affiliation:

1. Faculty of Engineering, Free University of Bozen-Bolzano, Piazza Università, Bolzano (BZ), Italy

2. Alupress AG, Bressanone (BZ), Italy

3. Covision Lab, Bressanone (BZ), Italy

4. Department of Industrial Engineering, University of Padua, Padua (PD), Italy

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/21693277.2024.2378199

Reference64 articles.

1. A cascading fuzzy logic with image processing algorithm–based defect detection for automatic visual inspection of industrial cylindrical object’s surface

2. Least-Squares Fitting of Two 3-D Point Sets

3. Image-based defect detection in lithium-ion battery electrode using convolutional neural networks

4. Quality prediction for aluminum diecasting process based on shallow neural network and data feature selection technique

5. Generalizing the Hough transform to detect arbitrary shapes

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