Main feature selection module.

<div><p>With the advancement of sensor technologies such as LiDAR and depth cameras, the significance of three-dimensional point cloud data in autonomous driving and environment sensing continues to increase.Point cloud registration stands as a fundamental task in constructing high-preci...

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Bibliographic Details
Main Author:	Yangzhuo Chen (21463876) (author)
Other Authors:	Fengjiao Guo (5962724) (author), Jingang Liu (490858) (author), Siling Dai (21463879) (author), Jia Huang (42138) (author), Xiaowen Cai (14337369) (author)
Published:	2025
Subjects:	Medicine Cell Biology Molecular Biology Developmental Biology Space Science Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Information Systems not elsewhere classified stanford dataset validate precision environmental models modelnet40 dataset reveal mean absolute error including unseen shapes existing methods continue environment sensing continues effectiveness scoring network channel attention mechanism pointnetlk ), go dcp ), self fast global registration deep learning approaches enhances system robustness icp ), robust prnet ), supervised learning xlink "> synergistically combines study introduces sensor technologies proposed method performance advantage partial registration overlapping regions overlapping areas novel categories noisy environments nearest neighbor matching capabilities iterative distance idam ). fundamental task feature extraction despite advancements depth cameras demonstrate limitations comprehensive evaluations complex scenarios autonomous driving additional experiments
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Main feature selection module.

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