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Special Section Guest Editorial: Change Detection Using Multi-Source Remotely Sensed Imagery

Xin Huang, Jiayi Li, Francesca Bovolo, Qi Wang
<span title="2019-09-23">2019</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/kay2tsbijbawliu45dnhvyvgsq" style="color: black;">Remote Sensing</a> </i> &nbsp;
The presented results showed improved results when multi-source remote sensed data was used in change detection.  ...  the utilization of these technologies in a variety of geospatial applications.  ...  Special thanks are due to the reviewers who dedicated their time for providing valuable and constructive recommendations, and to the editorial team of Remote Sensing for their support.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/rs11192216">doi:10.3390/rs11192216</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ddzetus3lvfslc7u3yu4bscnme">fatcat:ddzetus3lvfslc7u3yu4bscnme</a> </span>
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2020 Index IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Vol. 13

<span title="">2020</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/b2n2tpw5ang73osulebz6bm4ju" style="color: black;">IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing</a> </i> &nbsp;
., +, JSTARS 2020 632-641 Refined Extraction Of Building Outlines From High-Resolution Remote Sensing Imagery Based on a Multifeature Convolutional Neural Network and Morphological Filtering.  ...  Bi, H., +, JSTARS 2020 4825-4835 Refined Extraction Of Building Outlines From High-Resolution Remote Sensing Imagery Based on a Multifeature Convolutional Neural Network and Morphological Filtering.  ...  A New Deep-Learning-Based Approach for Earthquake-Triggered Landslide Detection From Single-Temporal RapidEye Satellite Imagery. Yi, Y., +, JSTARS 2020  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/jstars.2021.3050695">doi:10.1109/jstars.2021.3050695</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ycd5qt66xrgqfewcr6ygsqcl2y">fatcat:ycd5qt66xrgqfewcr6ygsqcl2y</a> </span>
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DA-CapsUNet: A Dual-Attention Capsule U-Net for Road Extraction from Remote Sensing Imagery

Yongfeng Ren, Yongtao Yu, Haiyan Guan
<span title="2020-09-04">2020</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/kay2tsbijbawliu45dnhvyvgsq" style="color: black;">Remote Sensing</a> </i> &nbsp;
Recently, with the improvement in image resolutions and quality, remote sensing images have provided an important data source for road extraction tasks.  ...  By constructing a capsule U-Net architecture, the DA-CapsUNet can extract and fuse multiscale capsule features to recover a high-resolution and semantically strong feature representation.  ...  Remote Sens. 2020, 12, 2866  ... 
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Table of Contents

<span title="">2020</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/b2n2tpw5ang73osulebz6bm4ju" style="color: black;">IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing</a> </i> &nbsp;
: Extraterrestrial Sensing Deep Learning-Driven Detection and Mapping of Rockfalls on Mars 1189 Refined Extraction Of Building Outlines From High-Resolution Remote Sensing Imagery Based on a Multifeature  ...  Liao 1856 Automatic Building Extraction via Adaptive Iterative Segmentation With LiDAR Data and High Spatial Resolution Imagery Fusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  ...  He 1551 Classification of High-Spatial-Resolution Remote Sensing Scenes Method Using Transfer Learning and Deep Convolutional Neural Network . . . . . . . . . . . . . . . . . . . . . . . . . W.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/jstars.2020.3046663">doi:10.1109/jstars.2020.3046663</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/zqzyhnzacjfdjeejvzokfy4qze">fatcat:zqzyhnzacjfdjeejvzokfy4qze</a> </span>
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Discrimination of Earthquake-Induced Building Destruction from Space Using a Pretrained CNN Model

Min Ji, Lanfa Liu, Rongchun Zhang, Manfred F. Buchroithner
<span title="2020-01-14">2020</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/smrngspzhzce7dy6ofycrfxbim" style="color: black;">Applied Sciences</a> </i> &nbsp;
Very high-resolution satellite imagery plays a key role in retrieving building damage information since it captures imagery quickly and effectively after the disaster.  ...  The present study showed the potential of using the pretrained Convolutional Neural Network (CNN) model to identify collapsed buildings caused by earthquakes using very high-resolution satellite imagery  ...  Acknowledgements When I look back to the past four years, I would say that it is a big challenge with quite some uncertainty to be a PhD candidate.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/app10020602">doi:10.3390/app10020602</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/mysjwv5eqzfrfjxsc5wcuywvzm">fatcat:mysjwv5eqzfrfjxsc5wcuywvzm</a> </span>
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Efficient Occluded Road Extraction from High-Resolution Remote Sensing Imagery

Dejun Feng, Xingyu Shen, Yakun Xie, Yangge Liu, Jian Wang
<span title="2021-12-07">2021</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/kay2tsbijbawliu45dnhvyvgsq" style="color: black;">Remote Sensing</a> </i> &nbsp;
Additionally, the result proves the proposed method is effective at extracting roads from occluded areas.  ...  Road extraction is important for road network renewal, intelligent transportation systems and smart cities.  ...  Efficient Occluded Road Extraction from High- Resolution Remote Sensing Imagery. Remote Sens. 2021, 13, 4974. https:// 1.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/rs13244974">doi:10.3390/rs13244974</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/rr6zwwswgrbvhlamwbhrjleehm">fatcat:rr6zwwswgrbvhlamwbhrjleehm</a> </span>
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Scene Classification of Remotely Sensed Images using Optimized RSISC-16 Net Deep Convolutional Neural Network Model

P. Deepan, L. Sudha, K. Kalaivani, J. Ganesh
<span title="2022-02-01">2022</span> <i title="European Alliance for Innovation n.o."> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/y4l63sf5djh4zowjsurq6fija4" style="color: black;">EAI Endorsed Transactions on Scalable Information Systems</a> </i> &nbsp;
However, we found that there is significant variability, in order to improve the system efficiency in characterizing complex patterns in remote sensing imagery.  ...  Remote Sensing Image (RSI) analysis has seen a massive increase in popularity over the last few decades, due to the advancement of deep learning models.  ...  The dataset which was extracted from Google Earth and covers the high resolution remotely sensed images in more than 100 countries.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.4108/eai.1-2-2022.173292">doi:10.4108/eai.1-2-2022.173292</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/hams7xrkyjdlboofxecbdjgqme">fatcat:hams7xrkyjdlboofxecbdjgqme</a> </span>
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A Deep Learning Model with Capsules Embedded for High Resolution Image Classification

Yujuan Guo, Jingjuan Liao, Guozhuang Shen
<span title="">2020</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/b2n2tpw5ang73osulebz6bm4ju" style="color: black;">IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing</a> </i> &nbsp;
Classification of remote sensing (RS) images is a key technology for extracting information on ground objects using RS methods.  ...  Capsules-Unet slightly outperforms all other approaches with far fewer parameters, a reduction in parameters of over 81.8% compared with U-net and over 13.8% compared with Capsule network.  ...  INTRODUCTION C LASSIFICATION is a fundamental task in remote sensing (RS), and it is also a complex data processing process [1] . Image classification is similar to semantic segmentation tasks.  ... 
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Poppy Crop Height and Capsule Volume Estimation from a Single UAS Flight

Faheem Iqbal, Arko Lucieer, Karen Barry, Reuben Wells
<span title="2017-06-22">2017</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/kay2tsbijbawliu45dnhvyvgsq" style="color: black;">Remote Sensing</a> </i> &nbsp;
The objective of this study was to estimate poppy plant height and capsule volume with remote sensing using an Unmanned Aircraft System (UAS).  ...  High correlations were found between UAS-derived PH and poppy capsule volume (CV) at capsule formation stage (R 2 0.74), with relative error of 19.62%.  ...  analysis of the result; and F.I. wrote the paper with the guidance and contributions from A.L., K.B. and R.W.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/rs9070647">doi:10.3390/rs9070647</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/u3vighiykjdnpcvvhhiylzdf5i">fatcat:u3vighiykjdnpcvvhhiylzdf5i</a> </span>
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2019 Index IEEE Transactions on Geoscience and Remote Sensing Vol. 57

<span title="">2019</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/4odsbtjobjalfki6xxabjpdu6y" style="color: black;">IEEE Transactions on Geoscience and Remote Sensing</a> </i> &nbsp;
., +, TGRS Oct. 2019 8255-8261 Fully Convolutional Networks for Multisource Building Extraction From an Open Aerial and Satellite Imagery Data Set.  ...  ., +, TGRS Oct. 2019 8011-8025 Fully Convolutional Networks for Multisource Building Extraction From an Open Aerial and Satellite Imagery Data Set.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tgrs.2020.2967201">doi:10.1109/tgrs.2020.2967201</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/kpfxoidv5bgcfo36zfsnxe4aj4">fatcat:kpfxoidv5bgcfo36zfsnxe4aj4</a> </span>
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Remote Sensing Image Scene Classification Using CNN-CapsNet

Wei Zhang, Ping Tang, Lijun Zhao
<span title="2019-02-28">2019</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/kay2tsbijbawliu45dnhvyvgsq" style="color: black;">Remote Sensing</a> </i> &nbsp;
Remote sensing image scene classification is one of the most challenging problems in understanding high-resolution remote sensing images.  ...  Fortunately, capsule network (CapsNet), which is a novel network architecture that uses a group of neurons as a capsule or vector to replace the neuron in the traditional neural network and can encode  ...  First, a remote sensing image is fed into a CNN model, and the initial feature maps are extracted from the convolutional layers.  ... 
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Review on Active and Passive Remote Sensing Techniques for Road Extraction

Jianxin Jia, Haibin Sun, Changhui Jiang, Kirsi Karila, Mika Karjalainen, Eero Ahokas, Ehsan Khoramshahi, Peilun Hu, Chen Chen, Tianru Xue, Tinghuai Wang, Yuwei Chen (+1 others)
<span title="2021-10-21">2021</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/kay2tsbijbawliu45dnhvyvgsq" style="color: black;">Remote Sensing</a> </i> &nbsp;
In this paper, we provide a comprehensive review on road extraction based on various remote sensing data sources, including high-resolution images, hyperspectral images, synthetic aperture radar images  ...  Digital maps of road networks are a vital part of digital cities and intelligent transportation.  ...  [234] proposed a grid-structured urban road network extraction method using LiDAR data and high-resolution imagery.  ... 
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EfficientUNet+: A Building Extraction Method for Emergency Shelters Based on Deep Learning

Di You, Shixin Wang, Futao Wang, Yi Zhou, Zhenqing Wang, Jingming Wang, Yibing Xiong
<span title="2022-05-05">2022</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/kay2tsbijbawliu45dnhvyvgsq" style="color: black;">Remote Sensing</a> </i> &nbsp;
In this study, EfficientUNet+, an improved building extraction method from remote sensing images based on the UNet model, is proposed.  ...  Quickly and accurately extracting buildings from remote sensing images is essential for urban planning, change detection, and disaster management applications.  ...  Google building dataset of emergency shelters within the Fifth Ring Road of Beijing: The dataset uses Google's high-resolution remote sensing imagery with a spatial resolution of 0.23 m.  ... 
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Ensemble of Deep Learning-Based Multimodal Remote Sensing Image Classification Model on Unmanned Aerial Vehicle Networks

Gyanendra Prasad Joshi, Fayadh Alenezi, Gopalakrishnan Thirumoorthy, Ashit Kumar Dutta, Jinsang You
<span title="2021-11-22">2021</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ye33srllvnanjouxn4tmrfgjsq" style="color: black;">Mathematics</a> </i> &nbsp;
In addition, an ensemble of DL models, namely VGG-19, Capsule Network (CapsNet), and MobileNet, is used for feature extraction.  ...  The EDL-MMLCC technique aims to classify remote sensing images into the different cloud, shades, and land cover classes.  ...  The accessibility of higher resolution remote sensing data on a continuous temporal basis could be much more efficient to automatically extract land covers and on-Earth objects and monitor and map their  ... 
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Semantic Segmentation for Buildings of Large Intra-Class Variation in Remote Sensing Images with O-GAN

Shuting Sun, Lin Mu, Lizhe Wang, Peng Liu, Xiaolei Liu, Yuwei Zhang
<span title="2021-01-29">2021</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/kay2tsbijbawliu45dnhvyvgsq" style="color: black;">Remote Sensing</a> </i> &nbsp;
Deep learning with deep network structures and back-propagation optimization can automatically learn features of targets in high-resolution remote sensing images.  ...  Remote sensing building extraction is of great importance to many applications, such as urban planning and economic status assessment.  ...  Building extraction from remote sensing images has become an important way of acquiring information.  ... 
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