Enhanced large-scale building extraction evaluation: developing a two-level framework using proxy data and building matching

Deep learning-based building extraction methods have widespread applications in diverse fields. However, the evaluation of large-scale extraction results remains challenging, due to traditional evaluation metrics rely on manually created ground-truth samples and the lack of comprehensive reference-b...

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Bibliographic Details
Main Authors: Shenglong Chen, Yoshiki Ogawa, Chenbo Zhao, Yoshihide Sekimoto
Format: Article
Language:English
Published: Taylor & Francis Group 2024-12-01
Series:European Journal of Remote Sensing
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Online Access:https://www.tandfonline.com/doi/10.1080/22797254.2024.2374844
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