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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Hlavní autoři:	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
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	MDPI AG 2021-11-01
Edice:	Applied Sciences
Témata:	machine learning video anomaly detection classification pattern recognition weakly supervised learning
On-line přístup:	https://www.mdpi.com/2076-3417/11/22/10861
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