Land-use/land-cover change detection based on a Siamese global learning framework for high spatial resolution remote sensing imagery

Q Zhu, X Guo, W Deng, S Shi, Q Guan, Y Zhong… - ISPRS Journal of …, 2022 - Elsevier
Due to the abundant features of high spatial resolution (HSR) remote sensing images,
change detection of these images is crucial to understanding the land-use and land-cover …

A global context-aware and batch-independent network for road extraction from VHR satellite imagery

Q Zhu, Y Zhang, L Wang, Y Zhong, Q Guan, X Lu… - ISPRS Journal of …, 2021 - Elsevier
Road extraction is to automatically label the pixels of roads in satellite imagery with specific
semantic categories based on the extraction of the topographical meaningful features. For …

A spectral-spatial-dependent global learning framework for insufficient and imbalanced hyperspectral image classification

Q Zhu, W Deng, Z Zheng, Y Zhong… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
Deep learning techniques have been widely applied to hyperspectral image (HSI)
classification and have achieved great success. However, the deep neural network model …

Building extraction from remote sensing images with sparse token transformers

K Chen, Z Zou, Z Shi - Remote Sensing, 2021 - mdpi.com
Deep learning methods have achieved considerable progress in remote sensing image
building extraction. Most building extraction methods are based on Convolutional Neural …

BOMSC-Net: Boundary optimization and multi-scale context awareness based building extraction from high-resolution remote sensing imagery

Y Zhou, Z Chen, B Wang, S Li, H Liu… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Automatic building extraction from high-resolution remote sensing imagery has various
applications, such as urban planning and land use management. However, the existing …

Res2-Unet, a new deep architecture for building detection from high spatial resolution images

F Chen, N Wang, B Yu, L Wang - IEEE Journal of Selected …, 2022 - ieeexplore.ieee.org
Accurate large-scale building detection is significant in monitoring urban development, map
updating, change detection, and digital city establishment. However, due to the complicated …

Self-attention in reconstruction bias U-Net for semantic segmentation of building rooftops in optical remote sensing images

Z Chen, D Li, W Fan, H Guan, C Wang, J Li - Remote sensing, 2021 - mdpi.com
Deep learning models have brought great breakthroughs in building extraction from high-
resolution optical remote-sensing images. Among recent research, the self-attention module …

Improved mask R-CNN for rural building roof type recognition from uav high-resolution images: a case study in hunan province, China

Y Wang, S Li, F Teng, Y Lin, M Wang, H Cai - Remote Sensing, 2022 - mdpi.com
Accurate roof information of buildings can be obtained from UAV high-resolution images.
The large-scale accurate recognition of roof types (such as gabled, flat, hipped, complex and …

Oil spill contextual and boundary-supervised detection network based on marine SAR images

Q Zhu, Y Zhang, Z Li, X Yan, Q Guan… - … on Geoscience and …, 2021 - ieeexplore.ieee.org
Oil spills have caused serious harm to the marine environment. Remote sensing technology
is one of the important tools for marine environment monitoring. Synthetic aperture radar …

[HTML][HTML] A comparative study of loss functions for road segmentation in remotely sensed road datasets

H Xu, H He, Y Zhang, L Ma, J Li - … Journal of Applied Earth Observation and …, 2023 - Elsevier
Road extraction from remote sensing imagery is a fundamental task in the field of image
semantic segmentation. For this goal, numerous supervised deep learning techniques have …