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pro vyhledávání: '"Luo, Yeqi"'
Arctic sea ice performs a vital role in global climate and has paramount impacts on both polar ecosystems and coastal communities. In the last few years, multiple deep learning based pan-Arctic sea ice concentration (SIC) forecasting methods have eme
Externí odkaz:
http://arxiv.org/abs/2410.14732
Autor:
Xu, Jingyi, Tu, Siwei, Yang, Weidong, Li, Shuhao, Liu, Keyi, Luo, Yeqi, Ma, Lipeng, Fei, Ben, Bai, Lei
Variation of Arctic sea ice has significant impacts on polar ecosystems, transporting routes, coastal communities, and global climate. Tracing the change of sea ice at a finer scale is paramount for both operational applications and scientific studie
Externí odkaz:
http://arxiv.org/abs/2410.09111
Self-supervised learning of point cloud aims to leverage unlabeled 3D data to learn meaningful representations without reliance on manual annotations. However, current approaches face challenges such as limited data diversity and inadequate augmentat
Externí odkaz:
http://arxiv.org/abs/2409.04963
Autor:
Zhou, Qingyuan, Yang, Weidong, Fei, Ben, Xu, Jingyi, Zhang, Rui, Liu, Keyi, Luo, Yeqi, He, Ying
Noise is an inevitable aspect of point cloud acquisition, necessitating filtering as a fundamental task within the realm of 3D vision. Existing learning-based filtering methods have shown promising capabilities on small-scale synthetic or real-world
Externí odkaz:
http://arxiv.org/abs/2404.05522