MRSSC: A BENCHMARK DATASET FOR MULTIMODAL REMOTE SENSING SCENE CLASSIFICATION [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2021 Scene classification based on multi-source remote sensing image is important for image interpretation, and has many applications, such as change detection, visual navigation and image retrieval. Deep learning has become a research hotspot in the field of
K. Liu +5 more
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Dense Attention Fluid Network for Salient Object Detection in Optical Remote Sensing Images [PDF]
IEEE Transactions on Image Processing, 2020 Despite the remarkable advances in visual saliency analysis for natural scene images (NSIs), salient object detection (SOD) for optical remote sensing images (RSIs) still remains an open and challenging problem.
Qijian Zhang +7 more
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ADVANCES IN OPTICAL POLARIZATION REMOTE SENSING FOR MARINE OBSERVATION: A CASE STUDY IN NANCHANG RIVER PARK [PDF]
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2022 Marine observation is a worldwide challenge, which implicates for a large number of social, economic and scientific problems. Satellite remote sensing provides incredible convenience for marine observation, and remote sensing techniques with different ...
F. Zhang +7 more
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RRNet: Relational Reasoning Network With Parallel Multiscale Attention for Salient Object Detection in Optical Remote Sensing Images [PDF]
IEEE Transactions on Geoscience and Remote Sensing, 2021 Salient object detection (SOD) for optical remote sensing images (RSIs) aims at locating and extracting visually distinctive objects/regions from the optical RSIs.
Runmin Cong +6 more
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Multi-Content Complementation Network for Salient Object Detection in Optical Remote Sensing Images [PDF]
IEEE Transactions on Geoscience and Remote Sensing, 2021 In the computer vision community, great progresses have been achieved in salient object detection from natural scene images (NSI-SOD); by contrast, salient object detection in optical remote sensing images (RSI-SOD) remains to be a challenging emerging ...
Gongyang Li +3 more
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Object Detection in Optical Remote Sensing Images: A Survey and A New Benchmark [PDF]
Isprs Journal of Photogrammetry and Remote Sensing, 2019 Substantial efforts have been devoted more recently to presenting various methods for object detection in optical remote sensing images. However, the current survey of datasets and deep learning based methods for object detection in optical remote ...
Ke Li +4 more
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An Oil Well Dataset Derived from Satellite-Based Remote Sensing
Remote Sensing, 2021 Estimation of the number and geo-location of oil wells is important for policy holders considering their impact on energy resource planning. With the recent development in optical remote sensing, it is possible to identify oil wells from satellite images.
Zhibao Wang +7 more
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Reconstruction Bias U-Net for Road Extraction From Optical Remote Sensing Images
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021 Automatic road extraction from remote sensing images plays an important role for navigation, intelligent transportation, and road network update, etc. Convolutional neural network (CNN)-based methods have presented many achievements for road extraction ...
Ziyi Chen +5 more
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Domain Adaptive Ship Detection in Optical Remote Sensing Images [PDF]
Remote Sensing, 2021 With the successful application of the convolutional neural network (CNN), significant progress has been made by CNN-based ship detection methods. However, they often face considerable difficulties when applied to a new domain where the imaging condition changes significantly.
Linhao Li +5 more
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Outlier Reconstruction of NDVI for Vegetation-Cover Dynamic Analyses
Applied Sciences, 2022 The normalized difference vegetation index (NDVI) contains important data for providing vegetation-cover information and supporting environmental analyses.
Zhengbao Sun +3 more
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