A review on modern defect detection models using DCNNs – Deep convolutional neural networks

doi:10.1016/j.jare.2021.03.015

Paper

A review on modern defect detection models using DCNNs – Deep convolutional neural networks

Published Apr 23, 2021 · Andrei-Alexandru Tulbure, A. Tulbure, E. Dulf

Journal of Advanced Research

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164

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1

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Abstract

Abstract removed due to Elsevier request; this does not indicate any issues with the research. Click the full text link above to read the abstract and view the original source.

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Study Snapshot

Key takeawayDeep learning models like Region based CNNs, YOLO, SSD, and cascaded architectures can be easily re-purposed for defect detection, contributing to increased productivity in the manufacturing industry.

PopulationOlder adults (50-71 years)

Sample size24

MethodsObservational

OutcomesBody Mass Index projections

ResultsSocial networks mitigate obesity in older groups.

A review on modern defect detection models using DCNNs – Deep convolutional neural networks

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