Continual BatchNorm Adaptation (CBNA) for Semantic Segmentation

Environment perception in autonomous driving vehicles often heavily relies on deep neural networks (DNNs), which are subject to domain shifts, leading to a significantly decreased performance during DNN deployment. Usually, this problem is addressed by unsupervised domain adaptation (UDA) approaches...

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Vydané v:	IEEE transactions on intelligent transportation systems Ročník 23; číslo 11; s. 20899 - 20911
Hlavní autori:	Klingner, Marvin, Ayache, Mouadh, Fingscheidt, Tim
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 01.11.2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Adaptation Adaptation models Artificial neural networks batch normalization Data models deep learning Delays Domain adaptation Domains Image segmentation Neural networks Semantic segmentation Semantics Task analysis unsupervised learning
ISSN:	1524-9050, 1558-0016
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