Results 21 to 30 of about 49,901 (265)
Generating Natural Adversarial Remote Sensing Images [PDF]
IEEE Transactions on Geoscience and Remote Sensing, 2022 Over the last years, Remote Sensing Images (RSI) analysis have started resorting to using deep neural networks to solve most of the commonly faced problems, such as detection, land cover classification or segmentation. As far as critical decision making can be based upon the results of RSI analysis, it is important to clearly identify and understand ...
Jean-Christophe Burnel +3 more
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Remote Sensing Image Information Quality Evaluation via Node Entropy for Efficient Classification
Remote Sensing, 2022 Combining remote sensing images with deep learning algorithms plays an important role in wide applications. However, it is difficult to have large-scale labeled datasets for remote sensing images because of acquisition conditions and costs.
Jiachen Yang +4 more
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Applied Sciences, 2023 Remote sensing scene classification (RSSC) is a very crucial subtask of remote sensing image understanding. With the rapid development of convolutional neural networks (CNNs) in the field of natural images, great progress has been made in RSSC.
Tao Xu, Zhicheng Zhao, Jun Wu
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REMOTE SENSING IMAGE CLASSIFICATION WITH THE SEN12MS DATASET [PDF]
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2021 Abstract. Image classification is one of the main drivers of the rapid developments in deep learning with convolutional neural networks for computer vision. So is the analogous task of scene classification in remote sensing. However, in contrast to the computer vision community that has long been using well-established, large-scale standard datasets to
M. Schmitt, M. Schmitt, Y.-L. Wu
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IEEE Access, 2020 Image super-resolution (SR) technique can improve the spatial resolution of images without upgrading the imaging system. As a result, SR promotes the development of high resolution (HR) remote sensing image applications.
Ning Zhang +4 more
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Multiscale Classification of Remote Sensing Images [PDF]
IEEE Transactions on Geoscience and Remote Sensing, 2012 A huge effort has been applied in image classification to create high-quality thematic maps and to establish precise inventories about land cover use. The peculiarities of remote sensing images (RSIs) combined with the traditional image classification challenges made RSI classification a hard task.
Jefersson Alex dos Santos +4 more
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Remote Sensing Image Change Detection With Transformers [PDF]
IEEE Transactions on Geoscience and Remote Sensing, 2022 Modern change detection (CD) has achieved remarkable success by the powerful discriminative ability of deep convolutions. However, high-resolution remote sensing CD remains challenging due to the complexity of objects in the scene. Objects with the same semantic concept may show distinct spectral characteristics at different times and spatial locations.
Hao Chen 0045 +2 more
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Target Detection Method for Low-Resolution Remote Sensing Image Based on ESRGAN and ReDet
Photonics, 2021 With the widespread use of remote sensing images, low-resolution target detection in remote sensing images has become a hot research topic in the field of computer vision.
Yuwu Wang, Guobing Sun, Shengwei Guo
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Neural Radiance Fields for High-Resolution Remote Sensing Novel View Synthesis
Remote Sensing, 2023 Remote sensing images play a crucial role in remote sensing target detection and 3D remote sensing modeling, and the enhancement of resolution holds significant application implications.
Junwei Lv +4 more
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IEEE Access, 2020 Road edge detection from remote sensing images, as an important ground object type, plays an important role in people’s life and travel and urban planning and development, and extracting road information from remote sensing images has practical ...
Chen Guobin, Zengwu Sun, Li Zhang
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