Spatio-Temporal Deep Learning-Based Methods for Defect Detection: An Industrial Application Study Case

Spatio-Temporal Deep Learning-Based Methods for Defect Detection: An Industrial Application Study Case

Data-driven methods—particularly machine learning techniques—are expected to play a key role in the headway of Industry 4.0. One increasingly popular application in this context is when anomaly detection is employed to test manufactured goods in assembly lines. In this work, we compare supervised, s...

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Bibliographic Details
Main Authors: Lucas A. da Silva, Eulanda M. dos Santos, Leo Araújo, Natalia S. Freire, Max Vasconcelos, Rafael Giusti, David Ferreira, Anderson S. Jesus, Agemilson Pimentel, Caio F. S. Cruz, Ruan J. S. Belem, André S. Costa, Osmar A. da Silva
Format: Article
Language:English
Published: MDPI AG 2021-11-01
Series:Applied Sciences
Subjects:
machine learning
video anomaly detection
classification
pattern recognition
weakly supervised learning
Online Access:https://www.mdpi.com/2076-3417/11/22/10861

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https://www.mdpi.com/2076-3417/11/22/10861

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