Results 11 to 20 of about 57,062 (333)
Remote Sensing, 2021 Compared with traditional optical and multispectral remote sensing images, hyperspectral images have hundreds of bands that can provide the possibility of fine classification of the earth’s surface.
Jianmei Ling, Lu Li, Haiyan Wang
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SYNERGETICS FRAMEWORK FOR HYPERSPECTRAL IMAGE CLASSIFICATION [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2013 Abstract. In this paper a new classification technique for hyperspectral data based on synergetics theory is presented. Synergetics – originally introduced by the physicist H. Haken – is an interdisciplinary theory to find general rules for pattern formation through selforganization and has been successfully applied in fields ranging from biology to ...
Müller, Rupert +2 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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Remote Sensing, 2023 Hyperspectral image classification plays a crucial role in various remote sensing applications. However, existing methods often struggle with the challenge of unknown classes, leading to decreased classification accuracy and limited generalization.
Huaming Zhou +4 more
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Vector Attribute Profiles for Hyperspectral Image Classification [PDF]
IEEE Transactions on Geoscience and Remote Sensing, 2016 Morphological attribute profiles are among the most prominent spectral–spatial pixel description methods. They are efficient, effective, and highly customizable multiscale tools based on hierarchical representations of a scalar input image. Their application to multivariate images in general and hyperspectral images in particular has been so far ...
Aptoula, Erchan +2 more
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Delving Into Classifying Hyperspectral Images via Graphical Adversarial Learning
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020 Recent remote sensing literature has seen generative adversarial network (GAN)-based models developed for hyperspectral image classification, especially in a spatiospectral manner.
Guangxing Wang, Peng Ren
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Remote Sensing, 2023 Crop classification of large-scale agricultural land is crucial for crop monitoring and yield estimation. Hyperspectral image classification has proven to be an effective method for this task.
Jiaxing Xie +9 more
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Customizing kernel functions for SVM-based hyperspectral image classification [PDF]
, 2008 Previous research applying kernel methods such as support vector machines (SVMs) to hyperspectral image classification has achieved performance competitive with the best available algorithms.
Baofeng Guo +4 more
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Advances in Hyperspectral Image Classification: Earth monitoring with statistical learning methods [PDF]
, 2013 Hyperspectral images show similar statistical properties to natural grayscale or color photographic images. However, the classification of hyperspectral images is more challenging because of the very high dimensionality of the pixels and the small number
Benediktsson, Jón Atli +3 more
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Linear vs Nonlinear Extreme Learning Machine for Spectral-Spatial Classification of Hyperspectral Image [PDF]
, 2017 As a new machine learning approach, extreme learning machine (ELM) has received wide attentions due to its good performances. However, when directly applied to the hyperspectral image (HSI) classification, the recognition rate is too low. This is because
Cao, Faxian +4 more
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