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TUH-NAS: A Triple-Unit NAS Network for Hyperspectral Image Classification [PDF]
SensorsOver the last few years, neural architecture search (NAS) technology has achieved good results in hyperspectral image classification. Nevertheless, existing NAS-based classification methods have not specifically focused on the complex connection between ...
Feng Chen, Baishun Su, Zongpu Jia
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THE DETECTION OF CONCEALED TARGETS IN WOODLAND AREAS USING HYPERSPECTRAL IMAGERY [PDF]
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2020 Recent innovations in microelectronic and semiconductor technology enable the creation of smaller and economical hyperspectral cameras. A filter combined camera with advanced scanning module is a game changer that extends the application of miniature ...
S. A. Rodriguez Gonzalez +6 more
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The Influence of Image Degradation on Hyperspectral Image Classification
Remote Sensing, 2022 Recent advances in hyperspectral remote sensing techniques, especially in the hyperspectral image classification techniques, have provided efficient support for recognizing and analyzing ground objects.
Congyu Li +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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3D RECONSTRUCTION FROM UAV-BASED HYPERSPECTRAL IMAGES [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2018 Reconstructing the 3D profile from a set of UAV-based images can obtain hyperspectral information, as well as the 3D coordinate of any point on the profile. Our images are captured from the Cubert UHD185 (UHD) hyperspectral camera, which is a new type of
L. Liu, L. Xu, J. Peng
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Contrastive Learning Based on Transformer for Hyperspectral Image Classification
Applied Sciences, 2021 Recently, deep learning has achieved breakthroughs in hyperspectral image (HSI) classification. Deep-learning-based classifiers require a large number of labeled samples for training to provide excellent performance.
Xiang Hu +4 more
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Research and Application of Several Key Techniques in Hyperspectral Image Preprocessing
Frontiers in Plant Science, 2021 This paper focuses on image segmentation, image correction and spatial-spectral dimensional denoising of images in hyperspectral image preprocessing to improve the classification accuracy of hyperspectral images.
Yu-hang Li +15 more
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HYPERSPECTRAL IMAGE DENOISING WITH CUBIC TOTAL VARIATION MODEL [PDF]
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2012 Image noise is generated unavoidably in the hyperspectral image acquision process and has a negative effect on subsequent image analysis. Therefore, it is necessary to perform image denoising for hyperspectral images.
H. Zhang
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Sensors, 2021 Hyperspectral image (HSI) classification is the subject of intense research in remote sensing. The tremendous success of deep learning in computer vision has recently sparked the interest in applying deep learning in hyperspectral image classification ...
Xiang Hu +4 more
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CatLC: Catalonia Multiresolution Land Cover Dataset
Scientific Data, 2022 Measurement(s) RGB orthophoto image • Infrared orthophoto image • Radar backscattering • Hyperspectral image • Topographic measurements • Landcover classification Technology Type(s) Airborne camera • Satellite SAR sensor • Satellite hyperspectral sensor •
Carlos García +3 more
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