DenseHybrid: Hybrid Anomaly Detection for Dense Open-set Recognition

Anomaly detection can be conceived either through generative modelling of regular training data or by discriminating with respect to negative training data. These two approaches exhibit different failure modes. Consequently, hybrid algorithms present an attractive research goal. Unfortunately, dense...

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Veröffentlicht in:	arXiv.org 2022-07
Hauptverfasser:	Grcić, Matej, Bevandić, Petra, Šegvić, Siniša
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Anomalies Back propagation Datasets Failure modes Image segmentation Normalizing Object recognition Training
Online-Zugang:	Volltext
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