Robotics & Machine Learning Daily News2024,Issue(Dec.11) :18-19.

Findings from KTH Royal Institute of Technology Reveals New Findings@@on Robotics and Automation (Uada3d: Unsupervised Adversarial@@Domain Adaptation for 3d Objec t Detection With Sparse Lidar@@and Large Domain Gaps)

Robotics & Machine Learning Daily News2024,Issue(Dec.11) :18-19.

Findings from KTH Royal Institute of Technology Reveals New Findings@@on Robotics and Automation (Uada3d: Unsupervised Adversarial@@Domain Adaptation for 3d Objec t Detection With Sparse Lidar@@and Large Domain Gaps)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – New research on Robotics - Robotics an d Automation is the subject of a report. Accordingto news reporting out of Stoc kholm, Sweden, by NewsRx editors, research stated, “In this study,we address a gap in existing unsupervised domain adaptation approaches on LiDAR-based 3D obje ct detection,which have predominantly concentrated on adapting between establis hed, high-density autonomousdriving datasets. We focus on sparser point clouds, capturing scenarios from different perspectives: not just from vehicles on the road but also from mobile robots on sidewalks, which encounter significantly different environmental conditions and sensor configurations.”

Key words

Stockholm/Sweden/Europe/Robotics and Automation/Robotics/KTH Royal Institute of Technology

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
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