Convolutional autoencoder based on latent subspace projection for anomaly detection

Image anomaly detection (AD) is widely researched on many occasions in computer vision tasks. High-dimensional data, such as image data, with noise and complex background is still challenging to detect anomalies under the situation that imbalanced or incomplete data are available. Some deep learning...

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Veröffentlicht in:	Methods (San Diego, Calif.) Jg. 214; S. 48 - 59
Hauptverfasser:	Yu, Qien, Li, Chen, Zhu, Ye, Kurita, Takio
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States Elsevier Inc 01.06.2023
Schlagworte:	Algorithms Anomaly detection Autoencoder computer vision data collection Latent subspace projection Subspace detection Subspace detection Autoencoder Latent subspace projection Anomaly detection
ISSN:	1046-2023, 1095-9130, 1095-9130
Online-Zugang:	Volltext
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