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Occlusion-aware road extraction network for high-resolution remote sensing imagery
Road occlusion seriously affects the connectivity of extracted roads, and has a negative
effect on practical applications. The dense road occlusion problem is caused by high-rise …
effect on practical applications. The dense road occlusion problem is caused by high-rise …
Full-level domain adaptation for building extraction in very-high-resolution optical remote-sensing images
Convolutional neural networks (CNNs) have achieved tremendous success in computer
vision tasks, such as building extraction. However, due to domain shift, the performance of …
vision tasks, such as building extraction. However, due to domain shift, the performance of …
Aerial image road extraction based on an improved generative adversarial network
Aerial photographs and satellite images are one of the resources used for earth observation.
In practice, automated detection of roads on aerial images is of significant values for the …
In practice, automated detection of roads on aerial images is of significant values for the …
Road extraction from a high spatial resolution remote sensing image based on richer convolutional features
The extraction and vectorization of roads from high spatial resolution remote sensing
(HSRRS) images are of great significance to city planning and development. However …
(HSRRS) images are of great significance to city planning and development. However …
Solo-to-collaborative dual-attention network for one-shot object detection in remote sensing images
In this article, we attempt to achieve one-shot object detection by mimicking the human
ability to learn new concepts under limited reference, which aims at detecting all object …
ability to learn new concepts under limited reference, which aims at detecting all object …