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Discriminative Context-Aware Network for Target Extraction in Remote Sensing Imagery

Lei Hu, Chuang Niu, Shenghan Ren, Minghao Dong, Changli Zheng, Wei Zhang, Jimin Liang
2021 IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing  
Based on the observations, we propose a novel discriminative context-aware network, named DCANet, for automatic target extraction in remote sensing imagery.  ...  Discriminative Context-Aware Network for Target Extraction in Remote Sensing Imagery Lei Hu, Chuang Niu, Shenghan Ren, Minghao Dong, Changli Zheng, Wei Zhang, and Jimin Liang, Member, IEEE Abstract-Extracting  ... 
doi:10.1109/jstars.2021.3138187 fatcat:6t6b6hqv4rderleog4n55xqkea

State-of-the-art and gaps for deep learning on limited training data in remote sensing [article]

John E. Ball, Derek T. Anderson, Pan Wei
2018 arXiv   pre-print
However, most remote sensing applications only have limited training data, of which a small subset is labeled.  ...  The last is generative adversarial networks, which can generate realistic looking data that can fool the likes of both a deep learning network and human.  ...  target domains, and v) how does transfer learning work in the context of multisensor fusion for remote sensing?  ... 
arXiv:1807.11573v1 fatcat:q6vtrod6nvgtrihjafo25iz3wi

Table of contents

2020 IEEE Geoscience and Remote Sensing Letters  
Huang 631 A Intelligent and Cognitive Computing for Remote Sensing Image Acquisition and Interpretation Target Detection in Hyperspectral Imagery via Sparse and Dense Hybrid Representation .......  ...  Zhou 716 Advanced Processing for Multimodal Optical Remote Sensing Imagery Multi-Scale Local Context Embedding for LiDAR Point Cloud Classification .............................................. ......  ... 
doi:10.1109/lgrs.2020.2979539 fatcat:d5qdtstyybavbjtj2ec34dgbo4

CAD-Net: A Context-Aware Detection Network for Objects in Remote Sensing Imagery [article]

Gongjie Zhang, Shijian Lu, Wei Zhang
2019 arXiv   pre-print
This paper presents a novel object detection network (CAD-Net) that exploits attention-modulated features as well as global and local contexts to address the new challenges in detecting objects from remote  ...  In addition, it designs a spatial-and-scale-aware attention module that guides the network to focus on more informative regions and features as well as more appropriate feature scales.  ...  object detection in remote sensing imagery.  ... 
arXiv:1903.00857v1 fatcat:d7beh37kevfkdajnobwjpayagm

2020 Index IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Vol. 13

2020 IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing  
., +, JSTARS 2020 4325-4338 A Discriminative Distillation Network for Cross-Source Remote Sensing Image Retrieval.  ...  ., +, JSTARS 2020 4325-4338 A Discriminative Distillation Network for Cross-Source Remote Sensing Image Retrieval.  ...  A New Deep-Learning-Based Approach for Earthquake-Triggered Landslide Detection From Single-Temporal RapidEye Satellite Imagery. Yi, Y., +, JSTARS 2020  ... 
doi:10.1109/jstars.2021.3050695 fatcat:ycd5qt66xrgqfewcr6ygsqcl2y

MKANet: An Efficient Network with Sobel Boundary Loss for Land-Cover Classification of Satellite Remote Sensing Imagery

Zhiqi Zhang, Wen Lu, Jinshan Cao, Guangqi Xie
2022 Remote Sensing  
Aimed at the characteristics of top view high-resolution remote sensing imagery, MKANet utilizes sharing kernels to simultaneously and equally handle ground segments of inconsistent scales, and also employs  ...  In response to the above weaknesses, we present an efficient lightweight semantic segmentation network termed MKANet.  ...  in remote sensing imagery.  ... 
doi:10.3390/rs14184514 fatcat:deh4ujrwdjf7blawy6cwwfr3ru

2021 Index IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Vol. 14

2021 IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing  
The Author Index contains the primary entry for each item, listed under the first author's name.  ...  -that appeared in this periodical during 2021, and items from previous years that were commented upon or corrected in 2021.  ...  ., +, JSTARS 2021 9768-9780 Boundary-Aware Multitask Learning for Remote Sensing Imagery.  ... 
doi:10.1109/jstars.2022.3143012 fatcat:dnetkulbyvdyne7zxlblmek2qy

Table of Contents

2020 IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing  
: 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  ...  Yunshan 1714 Shallow-Deep Convolutional Network and Spectral-Discrimination-Based Detail Injection for Multispectral Imagery Pan-Sharpening .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  ...  Fang 5297 BAS 4 Net: Boundary-Aware Semi-Supervised Semantic Segmentation Network for Very High Resolution Remote Sensing Images . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  ... 
doi:10.1109/jstars.2020.3046663 fatcat:zqzyhnzacjfdjeejvzokfy4qze

The Eyes of the Gods: A Survey of Unsupervised Domain Adaptation Methods Based on Remote Sensing Data

Mengqiu Xu, Ming Wu, Kaixin Chen, Chuang Zhang, Jun Guo
2022 Remote Sensing  
a fine-grained taxonomy of UDA methods applied for remote sensing data, which includes Generative training, Adversarial training, Self-training and Hybrid training methods, to better assist scholars in  ...  Finally, we describe the potential deficiencies and further in-depth insights of UDA in the field of remote sensing.  ...  Generative training methods applied in a remote sensing scene are more frequent than in a nature scene due to the larger discrepancy of remote sensing imagery compared with that of natural imagery, where  ... 
doi:10.3390/rs14174380 fatcat:4o6kc2jrwvaupcpehpdza7deou

SW-GAN: Road Extraction from Remote Sensing Imagery Using Semi-Weakly Supervised Adversarial Learning

Hao Chen, Shuang Peng, Chun Du, Jun Li, Songbing Wu
2022 Remote Sensing  
To make full use of the weak annotations, we propose a novel semi-weakly supervised method based on adversarial learning to extract road networks from remote sensing imagery.  ...  Road networks play a fundamental role in our daily life. It is of importance to extract the road structure in a timely and precise manner with the rapid evolution of urban road structure.  ...  Acknowledgments: The authors would also like to thank the anonymous referees for their valuable comments and helpful suggestions. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/rs14174145 fatcat:benp74lau5dk3ospqvmzpskibu

Table of contents

2020 IEEE Transactions on Geoscience and Remote Sensing  
Hu 5764 Region-Enhanced Convolutional Neural Network for Object Detection in Remote Sensing Images ..................... ................................................................................  ...  Jackson 5264 High-Resolution SAR Image Classification Using Context-Aware Encoder Network and Hybrid Conditional Random Field Model .....................................................................  ... 
doi:10.1109/tgrs.2020.3003196 fatcat:zbz435hg2nfm5ejpetz3xg3yyu

Object Tracking Based on Satellite Videos: A Literature Review

Zhaoxiang Zhang, Chenghang Wang, Jianing Song, Yuelei Xu
2022 Remote Sensing  
However, satellite video-based target tracking is a challenging research topic in remote sensing due to its relatively low spatial and temporal resolution.  ...  Finally, a revised multi-level dataset based on wpafb videos is generated and quantitatively evaluated for future development in the satellite video-based tracking area.  ...  Acknowledgments: We thank the anonymous reviewers and editors for their constructive comments and suggestions, which helped us to improve the manuscript.  ... 
doi:10.3390/rs14153674 fatcat:fhpk7dx6iba55msd3o2kaxppa4

Multi-Object Segmentation in Complex Urban Scenes from High-Resolution Remote Sensing Data

Abolfazl Abdollahi, Biswajeet Pradhan, Nagesh Shukla, Subrata Chakraborty, Abdullah Alamri
2021 Remote Sensing  
Deep convolutional models have displayed considerable performance for feature segmentation from remote sensing data in the recent years.  ...  Hence, this work's principal goal is to introduce two novel deep convolutional models based on UNet family for multi-object segmentation, such as roads and buildings from aerial imagery.  ...  In recent years, CNN approaches have been applied in remote sensing applications. For example, Ref.  ... 
doi:10.3390/rs13183710 fatcat:6arjszvmffdq7flht6wizaoz6a

2019 Index IEEE Transactions on Geoscience and Remote Sensing Vol. 57

2019 IEEE Transactions on Geoscience and Remote Sensing  
., Insect Biological Parameter Estimation Based on the Invariant Target Parameters of the Scattering Matrix; TGRS Aug. 2019 6212-6225 Hu, C., see Zhang, M., TGRS Sept. 2019 6666-6674 Hu, C., Zhang,  ...  Polar Format Algorithm for Curvilinear Spotlight SAR Imaging on Arbitrary Region of Interest; TGRS Oct. 2019 7995-8010 Hu, T., see Kang, Z., TGRS Jan. 2019 181-193 Hu, T., Wu, Y., Zheng, G., Zhang,  ...  Berveglieri, A., +, TGRS Nov. 2019 9252-9263 CAD-Net: A Context-Aware Detection Network for Objects in Remote Sensing Imagery.  ... 
doi:10.1109/tgrs.2020.2967201 fatcat:kpfxoidv5bgcfo36zfsnxe4aj4

Table of contents

2021 IEEE Transactions on Geoscience and Remote Sensing  
Plaza 6935 TCANet: Triple Context-Aware Network for Weakly Supervised Object Detection in Remote Sensing Images ....... .................................................................................  ...  Du 6894 Two-Stream Convolutional Networks for Hyperspectral Target Detection ................ D. Zhu, B. Du, and L.  ... 
doi:10.1109/tgrs.2021.3090240 fatcat:kbcbgsnrv5fuzbozvjynhj3c3y
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