Research Progress of Weld Tracking Image Processing Technology Based on Deep Learning Theory
Research Progress of Weld Tracking Image Processing Technology Based on Deep Learning Theory
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Author / Creator
Publisher
Sciendo
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Language
English
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Publisher
Sciendo
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Scope and Contents
Contents
In this paper, a convolutional neural network is used to localize the weld seam feature points with noise interference in complex welding environments. A priori frames are introduced into the feature point extraction network, combined with position prediction and confidence prediction, to improve the accuracy and anti-interference ability of the we...
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Full title
Research Progress of Weld Tracking Image Processing Technology Based on Deep Learning Theory
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Record Identifier
TN_cdi_crossref_primary_10_2478_amns_2023_2_01613
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_crossref_primary_10_2478_amns_2023_2_01613
Other Identifiers
ISSN
2444-8656
E-ISSN
2444-8656
DOI
10.2478/amns.2023.2.01613
