Unsupervised anomaly detection for pome fruit quality inspection using X-ray radiography

[Display omitted] •X-ray radiographs were used to identify apple and pear fruit with internal disorders.•Classification was achieved by a fully convolutional autoencoder.•We evaluated our model on both simulated and real data.•Our model outperforms the traditional autoencoder architecture. A novel f...

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Veröffentlicht in:	Computers and electronics in agriculture Jg. 226; S. 109364
Hauptverfasser:	Tempelaere, Astrid, He, Jiaqi, Van Doorselaer, Leen, Verboven, Pieter, Nicolai, Bart, Valerio Giuffrida, Mario
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 01.11.2024
Schlagworte:	Anomaly detection Autoencoder Deep learning Food quality inspection X-ray imaging Deep learning Food quality inspection Autoencoder Anomaly detection X-ray imaging
ISSN:	0168-1699
Online-Zugang:	Volltext
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