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Global Estimation of Building-Integrated Facade and Rooftop Photovoltaic Potential by Integrating 3D Building Footprint and Spatio-Temporal Datasets

Autor: Yu, Qing, Dong, Kechuan, Guo, Zhiling, Li, Jiaxing, Tan, Hongjun, Jin, Yanxiu, Yuan, Jian, Zhang, Haoran, Liu, Junwei, Chen, Qi, Yan, Jinyue

This research tackles the challenges of estimating Building-Integrated Photovoltaics (BIPV) potential across various temporal and spatial scales, accounting for different geographical climates and urban morphology. We introduce a holistic methodology

Externí odkaz: http://arxiv.org/abs/2412.01291

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Enhancing Building Semantic Segmentation Accuracy with Super Resolution and Deep Learning: Investigating the Impact of Spatial Resolution on Various Datasets

Autor: Guo, Zhiling, Shi, Xiaodan, Zhang, Haoran, Huang, Dou, Song, Xiaoya, Yan, Jinyue, Shibasaki, Ryosuke

The development of remote sensing and deep learning techniques has enabled building semantic segmentation with high accuracy and efficiency. Despite their success in different tasks, the discussions on the impact of spatial resolution on deep learnin

Externí odkaz: http://arxiv.org/abs/2307.04101

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Real-World Video for Zoom Enhancement based on Spatio-Temporal Coupling

Autor: Guo, Zhiling, Zheng, Yinqiang, Zhang, Haoran, Shi, Xiaodan, Cai, Zekun, Shibasaki, Ryosuke, Yan, Jinyue

In recent years, single-frame image super-resolution (SR) has become more realistic by considering the zooming effect and using real-world short- and long-focus image pairs. In this paper, we further investigate the feasibility of applying realistic

Externí odkaz: http://arxiv.org/abs/2306.13875

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