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Collaborative learning for hyperspectral image classification
Neurocomputing, 2018Abstract Recently, collaborative learning (CL) is introduced to combine active learning (AL) with semi-supervised learning (SSL), and solve the problem of limited training samples. In this paper, we proposed a novel CL framework for hyperspectral image classification, in which AL and SSL are collaboratively integrated using clustering (CLUC).
Chao Pan 0006 +3 more
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Segmentation as postprocessing for hyperspectral image classification
IEEE EUROCON 2015 - International Conference on Computer as a Tool (EUROCON), 2015Hyperspectral imaging is a new technique in remote sensing that collects hundreds of images at differents wavelength values for the same area of the Earth. For instance the Airborne Visible Infra-Red Imaging Spectrometer (AVIRIS) sensor of NASA capable to obtain 224 spectral channels in a wavelength range between 40 and 250 nanometers. As a result each
Luis-Ignacio Jimenez +5 more
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Feature Mining for Hyperspectral Image Classification
Proceedings of the IEEE, 2013Hyperspectral sensors record the reflectance from the Earth's surface over the full range of solar wavelengths with high spectral resolution. The resulting high-dimensional data contain rich information for a wide range of applications. However, for a specific application, not all the measurements are important and useful.
Xiuping Jia +2 more
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Hyperspectral Image Transformer Classification Networks
IEEE Transactions on Geoscience and Remote Sensing, 2022Xiaofei Yang 0002 +3 more
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Efficient SpectralFormer for hyperspectral image classification
Digital Signal Processing, 2023Weiliang Huang +4 more
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Hyperspectral Image Classification With Mamba
IEEE Transactions on Geoscience and Remote SensingZhaojie Pan +4 more
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Hyperspectral Image-Text Coupling Network For Hyperspectral Image Classification
IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing SymposiumJiaqi Yang 0005, Bo Du 0001
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Cross-domain hyperspectral image classification
Pattern RecognitionZhiyu Jiang +6 more
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