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Hyperspectral image classification: A benchmark
2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2017Hyperspectral image classification, an astonishing tool to distinguish the land covers in remote sensed hyperspectral images, has been investigated by multiple disciplines such as geoscience, environmental science, mathematics, and computer vision.
Xudong Kang +2 more
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Hierarchical classification systems for hyperspectral image classification
2007 IEEE International Geoscience and Remote Sensing Symposium, 2007In this study, we proposed some alternatives for building a binary hierarchical classification (BHC) systems. Two criteria for building the hierarchical tree under the idea of max-cut are addressed and two additional classification architectures based on the constructed trees are also proposed.
null Bor-Chen Kuo +3 more
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Hyperspectral Image Classification with Kernels
2007The information contained in hyperspectral images allows the characterization, identification, and classification of land covers with improved accuracy and robustness. However, several critical problems should be considered in the classification of hyperspectral images, among which are (a) the high number of spectral channels, (b) the spatial ...
Bruzzone, Lorenzo +3 more
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Kernel-based methods for hyperspectral image classification
IEEE Transactions on Geoscience and Remote Sensing, 2005This paper presents the framework of kernel-based methods in the context of hyperspectral image classification, illustrating from a general viewpoint the main characteristics of different kernel-based approaches and analyzing their properties in the hyperspectral domain.
G. Camps valls, Bruzzone, Lorenzo
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Hyperspectral Image Classification Using Functional Data Analysis
IEEE Transactions on Cybernetics, 2014The large number of spectral bands acquired by hyperspectral imaging sensors allows us to better distinguish many subtle objects and materials. Unlike other classical hyperspectral image classification methods in the multivariate analysis framework, in this paper, a novel method using functional data analysis (FDA) for accurate classification of ...
Hong, Li +4 more
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Hyperspectral image classification using spectral-spatial LSTMs
Neurocomputing, 2017Abstract In this paper, we propose a hyperspectral image (HSI) classification method using spectral-spatial long short term memory (LSTM) networks. Specifically, for each pixel, we feed its spectral values in different channels into Spectral LSTM one by one to learn the spectral feature. Meanwhile, we firstly use principle component analysis (PCA) to
Feng Zhou +3 more
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Automated tea quality classification by hyperspectral imaging
Applied Optics, 2009A hyperspectral imaging technique was attempted to classify green tea. Five grades of green tea samples were attempted. A hyperspectral imaging system was developed for data acquisition of tea samples. Principal component analysis was performed on the hyperspectral data to determine three optimal band images.
Jiewen, Zhao +3 more
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Hyperspectral Image Classification Using Relevance Vector Machines
IEEE Geoscience and Remote Sensing Letters, 2007This letter presents a hyperspectral image classification method based on relevance vector machines (RVMs). Support vector machine (SVM)-based approaches have been recently proposed for hyperspectral image classification and have raised important interest.
Demir, Begum, S. Ertürk
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Optimizing Hyperspectral Imaging Classification
2023Guyang Zhang, Waleed Abdulla
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Hyperspectral Image Transformer Classification Networks
IEEE Transactions on Geoscience and Remote Sensing, 2022Xiaofei Yang +3 more
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