Advances in Hyperspectral Data Exploitation

Using hyperspectral imaging (HSI) to exploit data has been found in a wide variety of applications. This reprint book only presents a small glimpse of it. Many other important applications using HSI which have emerged in data exploitation are not covered in this reprint book. For example, such appli...

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Format: eBook
Language:English
Published: Basel MDPI - Multidisciplinary Digital Publishing Institute 2022
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Online Access:Open Access: DOAB: description of the publication
Open Access: DOAB, download the publication
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042 |a dc 
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072 7 |a TBX  |2 bicssc 
720 1 |a Chang, Chein-I  |4 edt 
720 1 |a Chang, Chein-I  |4 oth 
720 1 |a Li, Hsiao-Chi  |4 edt 
720 1 |a Li, Hsiao-Chi  |4 oth 
720 1 |a Li, Jiaojiao  |4 edt 
720 1 |a Li, Jiaojiao  |4 oth 
720 1 |a Li, Xiaorun  |4 edt 
720 1 |a Li, Xiaorun  |4 oth 
720 1 |a Song, Meiping  |4 edt 
720 1 |a Song, Meiping  |4 oth 
720 1 |a Wang, Lin  |4 edt 
720 1 |a Wang, Lin  |4 oth 
720 1 |a Wang, Yulei  |4 edt 
720 1 |a Wang, Yulei  |4 oth 
720 1 |a Yu, Chunyan  |4 edt 
720 1 |a Yu, Chunyan  |4 oth 
720 1 |a Yu, Haoyang  |4 edt 
720 1 |a Yu, Haoyang  |4 oth 
245 0 0 |a Advances in Hyperspectral Data Exploitation 
260 |a Basel  |b MDPI - Multidisciplinary Digital Publishing Institute  |c 2022 
300 |a 1 online resource (434 p.) 
336 |a text  |b txt  |2 rdacontent 
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338 |a online resource  |b cr  |2 rdacarrier 
506 0 |a Open Access  |f Unrestricted online access  |2 star 
520 |a Using hyperspectral imaging (HSI) to exploit data has been found in a wide variety of applications. This reprint book only presents a small glimpse of it. Many other important applications using HSI which have emerged in data exploitation are not covered in this reprint book. For example, such applications may include water pollution and toxic waste in environmental monitoring, pesticide residual detection in food safety and inspection, plant and crop disease detection in agriculture, tumor detection and breast cancer detection in medical imaging, drug traffic in law enforcement, etc. Nevertheless, this reprint book provides many techniques which may find their ways in these applications as well. 
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546 |a English 
650 7 |a History of engineering & technology  |2 bicssc 
650 7 |a Technology: general issues  |2 bicssc 
653 |a air temperature 
653 |a anomaly detection 
653 |a atmospheric transmittance 
653 |a attention mechanism 
653 |a band selection 
653 |a band selection (BS) 
653 |a boundary-aware constraint 
653 |a carbon dioxide absorption 
653 |a change detection 
653 |a channel augmented attention 
653 |a classification 
653 |a coffee beans 
653 |a color formation models 
653 |a constrained energy minimization (CEM) 
653 |a constrained sparse representation 
653 |a constrained-target optimal index factor band selection (CTOIFBS) 
653 |a constraint representation 
653 |a convolutional neural network 
653 |a data augmentation 
653 |a data fusion 
653 |a deep convolutional neural networks 
653 |a deep learning 
653 |a denoising 
653 |a emissivity 
653 |a evolutionary computation 
653 |a FTIR 
653 |a fused features 
653 |a generative adversarial network 
653 |a heuristic algorithms 
653 |a hyperspectral 
653 |a hyperspectral image 
653 |a hyperspectral image classification 
653 |a hyperspectral image few-shot classification 
653 |a hyperspectral image super-resolution 
653 |a hyperspectral imagery 
653 |a hyperspectral imagery classification 
653 |a hyperspectral images 
653 |a hyperspectral imaging 
653 |a hyperspectral imaging (HSI) 
653 |a hyperspectral imaging data 
653 |a hyperspectral reconstruction 
653 |a hyperspectral remote sensing 
653 |a hyperspectral target detection 
653 |a hyperspectral unmixing 
653 |a image classification 
653 |a image fusion 
653 |a insect damage 
653 |a joint tensor decomposition 
653 |a least square estimation 
653 |a lightweight convolutional neural networks 
653 |a machine learning 
653 |a meta-learning 
653 |a midwave infrared 
653 |a mine environment 
653 |a moving target detection 
653 |a multi-source image fusion 
653 |a multiscale decision fusion 
653 |a multispectral image 
653 |a MWIR 
653 |a nonlinear unmixing 
653 |a plug-and-play 
653 |a relation network 
653 |a residual augmented attentional u-shape network 
653 |a rice 
653 |a rice leaf blast 
653 |a rice leaf folder 
653 |a self-supervised learning 
653 |a self-supervised training 
653 |a separation 
653 |a SFIM 
653 |a spatial augmented attention 
653 |a spatial filter 
653 |a spatial measurement 
653 |a spatio-temporal processing 
653 |a spectral reconstruction 
653 |a spectral-spatial residual network 
653 |a superpixel segmentation 
653 |a target detection 
653 |a temperature 
653 |a transfer learning 
653 |a underwater hyperspectral target detection 
653 |a underwater spectral imaging system 
653 |a unmanned aerial vehicles (UAVs) 
653 |a upland swamps 
653 |a vegetation 
653 |a vegetation mapping 
653 |a visualization 
793 0 |a DOAB Library. 
856 4 0 |u https://directory.doabooks.org/handle/20.500.12854/94557  |7 0  |z Open Access: DOAB: description of the publication 
856 4 0 |u https://mdpi.com/books/pdfview/book/6392  |7 0  |z Open Access: DOAB, download the publication