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Published in 2020 at "Arabian Journal of Geosciences"
DOI: 10.1007/s12517-020-05487-4
Abstract: Creating accurate land use and land cover maps using remote sensing images is one of the most important applications of remotely sensed data. Abundant spectral information in hyperspectral images (HSI) makes it possible to distinguish…
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Keywords:
feature;
spectral spatial;
classification hyperspectral;
spatial features ... See more keywords
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Published in 2018 at "Journal of the Indian Society of Remote Sensing"
DOI: 10.1007/s12524-018-0908-6
Abstract: In this paper, we propose a new sparsity-based approach for the spectral–spatial classification of hyperspectral imagery. The proposed approach exploits the sparse representations of the spectral and spatial information contained in the data to generate…
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Keywords:
representations spectral;
classification;
spectral spatial;
classification hyperspectral ... See more keywords
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Published in 2018 at "Isprs Journal of Photogrammetry and Remote Sensing"
DOI: 10.1016/j.isprsjprs.2017.10.006
Abstract: Abstract Spectral-spatial classification is known to be an effective way to improve classification performance by integrating spectral information and spatial cues for hyperspectral imagery. In this paper, a game-theoretic spectral-spatial classification algorithm (GTA) using a…
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Keywords:
game;
classification;
spectral spatial;
cooperative game ... See more keywords
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Published in 2019 at "Scientific Reports"
DOI: 10.1038/s41598-019-43971-4
Abstract: Automatic carcinoma detection from hyper/multi spectral images is of essential importance due to the fact that these images cannot be presented directly to the clinician. However, standard approaches for carcinoma detection use hundreds or even…
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Keywords:
spectral spatial;
spatial variation;
carcinoma detection;
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Published in 2023 at "International Journal of Remote Sensing"
DOI: 10.1080/01431161.2023.2203340
Abstract: ABSTRACT Deep learning methods have shown great advantages in hyperspectral image (HSI) classification tasks. In particular, convolutional neural network (CNN)-based methods for HSI classification have made great progress. However, it is difficult for CNN to…
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Keywords:
network;
multi scale;
classification;
spectral spatial ... See more keywords
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Published in 2018 at "IEEE Access"
DOI: 10.1109/access.2018.2884501
Abstract: Dimension reduction (DR) is an essential preprocessing for hyperspectral image (HSI) classification. Recently, nonnegative matrix factorization (NMF) has been shown as an effective tool for the DR of hyperspectral data given the fact that it…
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Keywords:
dimension;
spectral spatial;
dimension reduction;
nonnegative matrix ... See more keywords
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Published in 2019 at "IEEE Access"
DOI: 10.1109/access.2019.2925283
Abstract: In recent years, various deep learning-based methods have been applied in hyperspectral image (HSI) classification. Among them, spectral-spatial approaches have demonstrated their power to yield high accuracies. However, these methods tend to be computationally expensive.…
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Keywords:
ssdc densenet;
dual channel;
spectral spatial;
cost ... See more keywords
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Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3194260
Abstract: Marine oil spills accidents has caused a large amount of crude oil to leak into the marine environment and threaten marine ecological environment. Hyperspectral remote sensing images (HRSI) technology can quickly and accurately identify oil…
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Keywords:
neural networks;
oil;
spectral spatial;
convolutional neural ... See more keywords
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Published in 2022 at "Proceedings of the IEEE"
DOI: 10.1109/jproc.2022.3207576
Abstract: Forthcoming capacity scaling requirements of optical networks and advances in optical fiber communications beyond the omnipresent single-mode fiber operating over the conventional band introduces new opportunities and challenges for exploiting the expanded spectral and spatial…
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Keywords:
fiber optic;
spatial degrees;
spectral spatial;
degrees freedom ... See more keywords
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Published in 2017 at "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"
DOI: 10.1109/jstars.2016.2602305
Abstract: In hyperspectral image classification, both spectral and spatial data distributions are important in describing and identifying different materials and objects in the image. Furthermore, consistent spatial structures across bands can be useful in capturing inherent…
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Keywords:
image;
spectral spatial;
sparse coding;
hyperspectral image ... See more keywords
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Published in 2020 at "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"
DOI: 10.1109/jstars.2020.2982614
Abstract: Deep spectral–spatial features fusion has become a research focus in hyperspectral image (HSI) classification. However, how to extract more robust spectral–spatial features is still a challenging problem. In this article, a novel deep multilayer fusion…
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Keywords:
dense;
fusion;
spectral spatial;
hsi ... See more keywords