Multi-unit stacked architecture: An urban scene segmentation network based on UNet and ShuffleNetv2

Classic high-accuracy semantic segmentation models typically come with a large number of parameters, making them unsuitable for deployment on driverless platforms with limited computational power. To strike a balance between accuracy and limited computational budget, and enable the use of the classi...

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Veröffentlicht in:	Applied soft computing Jg. 165; S. 112065
Hauptverfasser:	Liu, Dian, Du, Jianchao, Li, Chuhan, Yu, Chenglong, Zhang, Mingjin
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 01.11.2024
Schlagworte:	Encoder and decoder Resource-constrained inference Semantic segmentation Unmanned driving Encoder and decoder Resource-constrained inference Semantic segmentation Unmanned driving
ISSN:	1568-4946
Online-Zugang:	Volltext
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