Semantic Segmentation of In-Vehicle Point Cloud With Improved RangeNet++ Loss Function

To solve the problem of inaccurate object segmentation caused by unbalanced samples for in-vehicle point cloud, an improved semantic segmentation network RangeNet++ based on asymmetric loss function (AsL-RangeNet++) is proposed, which uses asymmetric loss (AsL) function a...

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Detalhes bibliográficos

Principais autores:	Jinhui Zhang, Haiyan Jiang, Huizhi Shao, Qingjun Song, Xiaoshuang Wang, Dashuai Zong
Formato:	Artigo
Idioma:	Inglês
Publicado em:	IEEE 2023-01-01
coleção:	IEEE Access
Assuntos:	Semantic segmentation rangenet++ asymmetric loss function in-vehicle point cloud
Acesso em linha:	https://ieeexplore.ieee.org/document/10023475/
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