Occlusion-aware road extraction network for high-resolution remote sensing imagery

R Yang, Y Zhong, Y Liu, X Lu… - IEEE Transactions on …, 2024‏ - ieeexplore.ieee.org
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 …

Full-level domain adaptation for building extraction in very-high-resolution optical remote-sensing images

D Peng, H Guan, Y Zang… - IEEE Transactions on …, 2021‏ - ieeexplore.ieee.org
Convolutional neural networks (CNNs) have achieved tremendous success in computer
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

X Zhang, X Han, C Li, X Tang, H Zhou, L Jiao - Remote Sensing, 2019‏ - mdpi.com
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 …

Road extraction from a high spatial resolution remote sensing image based on richer convolutional features

Z Hong, D Ming, K Zhou, Y Guo, T Lu - IEEE Access, 2018‏ - ieeexplore.ieee.org
The extraction and vectorization of roads from high spatial resolution remote sensing
(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

L Li, X Yao, G Cheng, M Xu, J Han… - IEEE Transactions on …, 2021‏ - ieeexplore.ieee.org
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 …