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Compression of hyperspectral imagery via linear prediction
2006Motta et al., 2003) proposed a Locally Optimal Vector Quantizer (LPVQ) for lossless encoding of hyperspectral data, in particular, Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) images. In this paper we first show how it is possible to improve the baseline LPVQ algorithm via linear prediction techniques, band reordering and least squares ...
FRANCESCO RIZZO +3 more
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Using satellite imagery to understand and promote sustainable development
Science, 2021Marshall B Burke +2 more
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Target detection of hyperspectral imagery
Eighth Symposium on Novel Photoelectronic Detection Technology and Applications, 2022Hang Qu, Lei Xiao, Xinghua Hou
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Street view imagery in urban analytics and GIS: A review
Landscape and Urban Planning, 2021Filip Biljecki, Koichi Ito
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A review of deep learning methods for semantic segmentation of remote sensing imagery
Expert Systems With Applications, 2021Xiaohui Yuan
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Combining satellite imagery and machine learning to predict poverty
Science, 2016Neal Jean +2 more
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Decoding motor imagery from the posterior parietal cortex of a tetraplegic human
Science, 2015Tyson Aflalo +2 more
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Automated Water Extraction Index: A new technique for surface water mapping using Landsat imagery
Remote Sensing of Environment, 2014Gudina Legese Feyisa +2 more
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