72 citations · 118 across the 6 of their papers we have counts for
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cs.CV2023★ 1 cited
Detecting Novelties with Empty Classes
Svenja Uhlemeyer, Julian Lienen, Eyke Hüllermeier +1
For open world applications, deep neural networks (DNNs) need to be aware of previously unseen data and adaptable to evolving environments. Furthermore, it is desirable to detect a…
cs.RO2023★ 23 cited
Perception Datasets for Anomaly Detection in Autonomous Driving: A Survey
Daniel Bogdoll, Svenja Uhlemeyer, Kamil Kowol +1
Deep neural networks (DNN) which are employed in perception systems for autonomous driving require a huge amount of data to train on, as they must reliably achieve high performance…