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Intelligent Object Recognition of Urban Water Bodies Based on Deep Learning for Multi-Source and Multi-Temporal High Spatial Resolution Remote Sensing Imagery

机译：基于深度学习的多源和多时间高空间分辨率遥感图像智能对象识别城市水体

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Shiran Song; Jianhua Liu; Yuan Liu; Guoqiang Feng; Hui Han; Yuan Yao; Mingyi Du;
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1. Intelligent Object Recognition of Urban Water Bodies Based on Deep Learning for Multi-Source and Multi-Temporal High Spatial Resolution Remote Sensing Imagery [J] . Nature reviews Cancer . 2020,第2期

机译：基于深度学习的多源和多时间高空间分辨率遥感图像智能对象识别城市水体
2. Combining Pixel- and Object-Based Machine Learning for Identification of Water-Body Types From Urban High-Resolution Remote-Sensing Imagery [J] . Huang Xin, Xie Cong, Fang Xing, Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of . 2015,第5期

机译：结合基于像素和基于对象的机器学习，从城市高分辨率遥感影像中识别水体类型
3. National-scale greenhouse mapping for high spatial resolution remote sensing imagery using a dense object dual-task deep learning framework: A case study of China [J] . Ma Ailong, Chen Dingyuan, Zhong Yanfei, ISPRS Journal of Photogrammetry and Remote Sensing . 2021,第Nova期

机译：使用密集物体双任务深度学习框架的高空间分辨率遥感图像的全国规模温室映射 - 以中国为例
4. Deep Learning for Automatic Recognition of Oil Production Related Objects based on High-Resolution Remote Sensing Imagery [C] . Nannan Zhang, Hang Zhao, Yang Liu, International Geoscience and Remote Sensing Symposium . 2020

机译：基于高分辨率遥感图像的石油生产相关对象的深度学习
5. Characterizing scale-dependent spatial structure in multi-resolution, multi-temporal and hyperspectral remotely sensed imagery. [D] . Chen, Weirong. 2004

机译：在多分辨率，多时间和高光谱遥感影像中表征尺度依赖的空间结构。
6. A Sparse Dictionary Learning-Based Adaptive Patch Inpainting Method for Thick Clouds Removal from High-Spatial Resolution Remote Sensing Imagery [O] . Fan Meng, Xiaomei Yang, Chenghu Zhou, 2017

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7. Intelligent Mapping of Urban Forests from High-Resolution Remotely Sensed Imagery Using Object-Based U-Net-DenseNet-Coupled Network [O] . Shaobai He, Huaqiang Du, Guomo Zhou, 2020

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Intelligent Object Recognition of Urban Water Bodies Based on Deep Learning for Multi-Source and Multi-Temporal High Spatial Resolution Remote Sensing Imagery

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