Results 11 to 20 of about 352,126 (198)
IEEE Access, 2023 Since hyperspectral remote sensing images are three-dimensional data cubes with spatial and spectral information, with many wavebands and high inter-band correlation, the number of training samples required for classification is greatly increased.
Chaozhu Zhang +3 more
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IET Image Processing, 2022 Although hyperspectral data, especially spaceborne images, are rich in spectral information, their spatial resolution is usually low due to the limitation of sensor design and other factors.
Haoyang Yu +5 more
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Aggregated Deep Local Features for Remote Sensing Image Retrieval [PDF]
, 2019 Remote Sensing Image Retrieval remains a challenging topic due to the special nature of Remote Sensing Imagery. Such images contain various different semantic objects, which clearly complicates the retrieval task.
Bondarev, Egor +3 more
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Object-Based Land Cover Classification for ALOS Image Combining TM Spectral [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2013 Land cover classification for high spatial resolution remote sensing images becomes a challenging work. The high spatial resolution remote sensing images have more spatial information.
G. Wang, J. Liu, G. He
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A Novel Deep Nearest Neighbor Neural Network for Few-Shot Remote Sensing Image Scene Classification
Remote Sensing, 2023 Remote sensing image scene classification has become more and more popular in recent years. As we all know, it is very difficult and time-consuming to obtain a large number of manually labeled remote sensing images.
Yanqiao Chen +4 more
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Atmospheric Light Estimation Based Remote Sensing Image Dehazing
Remote Sensing, 2021 Remote sensing images are widely used in object detection and tracking, military security, and other computer vision tasks. However, remote sensing images are often degraded by suspended aerosol in the air, especially under poor weather conditions, such ...
Zhiqin Zhu +7 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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An Adaptive Semi-Parametric and Context-Based Approach to Unsupervised Change Detection in Multitemporal Remote-Sensing Images [PDF]
, 2002 In this paper, a novel automatic approach to the unsupervised identification of changes in multitemporal remote-sensing images is proposed. This approach, unlike classical ones, is based on the formulation of the unsupervised change-detection problem in ...
Bruzzone, Lorenzo +1 more
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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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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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