Boundary-Aware Adversarial Learning Domain Adaption and Active Learning for Cross-Sensor Building Extraction

The use of convolutional neural networks (CNNs) for building extraction from remote sensing images has been widely studied and many public datasets have been made available for accelerating development of these CNN models. Yet adapting pretrained models at scale in real-world scenarios remains a cha...

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Auteurs principaux:	Hsiuhan Lexie Yang, Nikhil Makkar, Melanie Laverdiere, Amy Rose
Format:	Artigo
Langue:	Inglês
Publié:	IEEE 2024-01-01
Collection:	IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Sujets:	Active learning adversarial learning building extraction domain adaptation uncertainty calibration
Accès en ligne:	https://ieeexplore.ieee.org/document/10505773/
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