Deep learning-based change detection in remote sensing images: A review
Images gathered from different satellites are vastly available these days due to the fast
development of remote sensing (RS) technology. These images significantly enhance the …
development of remote sensing (RS) technology. These images significantly enhance the …
Machine learning information fusion in Earth observation: A comprehensive review of methods, applications and data sources
This paper reviews the most important information fusion data-driven algorithms based on
Machine Learning (ML) techniques for problems in Earth observation. Nowadays we …
Machine Learning (ML) techniques for problems in Earth observation. Nowadays we …
DABNet: Deformable contextual and boundary-weighted network for cloud detection in remote sensing images
In recent years, deep convolutional neural networks (DCNNs) have made significant
progress in cloud detection tasks, and the detection accuracy has been greatly improved …
progress in cloud detection tasks, and the detection accuracy has been greatly improved …
Cloud and cloud shadow detection for optical satellite imagery: Features, algorithms, validation, and prospects
The presence of clouds prevents optical satellite imaging systems from obtaining useful
Earth observation information and negatively affects the processing and application of …
Earth observation information and negatively affects the processing and application of …
2019 年中国陆表定量遥感发展综述
梁顺林， 白瑞， 陈晓娜， 程洁， 范闻捷， 何涛， 贾坤… - 遥感学报, 2021 - ygxb.ac.cn
为了更好地了解中国定量遥感的发展态势和加强同行之间的信息交流, 根据中国学者2019
年发表的SCI 检索论文和部分中文论文, 对陆表定量遥感的核心进展进行了总结 …
年发表的SCI 检索论文和部分中文论文, 对陆表定量遥感的核心进展进行了总结 …
Strip pooling channel spatial attention network for the segmentation of cloud and cloud shadow
Y Qu, M Xia, Y Zhang - Computers & Geosciences, 2021 - Elsevier
The background in image of remote sensing is often complicated and changeable, and the
edge of cloud and its shadow is irregular. In the traditional method, the bright part of the …
edge of cloud and its shadow is irregular. In the traditional method, the bright part of the …
Understanding cities with machine eyes: A review of deep computer vision in urban analytics
Modelling urban systems has interested planners and modellers for decades. Different
models have been achieved relying on mathematics, cellular automation, complexity, and …
models have been achieved relying on mathematics, cellular automation, complexity, and …
A review of landcover classification with very-high resolution remotely sensed optical images—Analysis unit, model scalability and transferability
As an important application in remote sensing, landcover classification remains one of the
most challenging tasks in very-high-resolution (VHR) image analysis. As the rapidly …
most challenging tasks in very-high-resolution (VHR) image analysis. As the rapidly …
Thick cloud and cloud shadow removal in multitemporal imagery using progressively spatio-temporal patch group deep learning
Thick cloud and its shadow severely reduce the data usability of optical satellite remote
sensing data. Although many approaches have been presented for cloud and cloud shadow …
sensing data. Although many approaches have been presented for cloud and cloud shadow …
Thin cloud removal in optical remote sensing images based on generative adversarial networks and physical model of cloud distortion
Cloud contamination is an inevitable problem in optical remote sensing images. Unlike thick
clouds, thin clouds do not completely block out background which makes it possible to …
clouds, thin clouds do not completely block out background which makes it possible to …