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Shaobo Xia

As seen in: Frontiers
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Articles

APCoTTA: Continual Test-Time Adaptation for Semantic Segmentation of Airborne LiDAR Point Clouds

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By Shaobo Xia, Sheng Nie
| arxiv.org
[Submitted on 15 May 2025 ( v1 ), last revised 17 Feb 2026 (this version, v2)] Title:APCoTTA: Continual Test-Time Adaptation for Semantic Segmentation of Airborne LiDAR Point Clouds View a PDF of the paper titled APCoTTA: Continual Test-Time Adaptation for Semantic Segmentation of Airborne LiDAR Point Clouds, by Yuan Gao and Shaobo Xia and Sheng Nie and Cheng Wang and Xiaohuan Xi and Bisheng Yang View PDF HTML (experimental) Abstract:Airborne laser scanning (ALS) point cloud semantic...
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Diffusion Models Meet Remote Sensing: Principles, Methods, and Perspectives

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By Jun Yue, Shaobo Xia, Pedram Ghamisi, Weiying Xie
| arxiv.org
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Forest emissions reduction assessment from airborne LiDAR data using multiple machine learning approaches

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By Joan R. Morante, Shaobo Xia, Feng Cheng, Shize Qin
| Frontiers
1 Introduction Mitigating climate change relies on Carbon Dioxide Removal (CDR) (van Vuuren et al., 2013; Kriegler et al., 2018). To meet the climate objective of restricting global climate change to 1.5°C–2°C, as stated by the Intergovernmental Panel on Climate Change (IPCC), the assessments of most models depend on the large-scale deployment of CDR technologies, and the dependence on CDR technologies increases with the delay of the emission peak (Roe et al., 2019).
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