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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.
Technology: general issues --- History of engineering & technology --- hyperspectral image few-shot classification --- deep learning --- meta-learning --- relation network --- convolutional neural network --- constrained-target optimal index factor band selection (CTOIFBS) --- hyperspectral image --- underwater spectral imaging system --- underwater hyperspectral target detection --- band selection (BS) --- constrained energy minimization (CEM) --- lightweight convolutional neural networks --- hyperspectral imagery classification --- transfer learning --- air temperature --- spatial measurement --- FTIR --- MWIR --- carbon dioxide absorption --- target detection --- coffee beans --- insect damage --- hyperspectral imaging --- band selection --- visualization --- color formation models --- multispectral image --- image fusion --- joint tensor decomposition --- anomaly detection --- constrained sparse representation --- hyperspectral imagery --- moving target detection --- spatio-temporal processing --- hyperspectral remote sensing --- image classification --- constraint representation --- superpixel segmentation --- multiscale decision fusion --- plug-and-play --- denoising --- nonlinear unmixing --- spectral reconstruction --- residual augmented attentional u-shape network --- spatial augmented attention --- channel augmented attention --- boundary-aware constraint --- atmospheric transmittance --- temperature --- emissivity --- separation --- midwave infrared --- hyperspectral images --- hyperspectral image super-resolution --- data fusion --- spectral-spatial residual network --- self-supervised training --- hyperspectral --- vegetation --- generative adversarial network --- data augmentation --- classification --- rice leaf blast --- hyperspectral imaging data --- deep convolutional neural networks --- fused features --- evolutionary computation --- heuristic algorithms --- machine learning --- unmanned aerial vehicles (UAVs) --- vegetation mapping --- upland swamps --- mine environment --- rice --- rice leaf folder --- hyperspectral image classification --- change detection --- self-supervised learning --- attention mechanism --- multi-source image fusion --- SFIM --- least square estimation --- spatial filter --- hyperspectral imaging (HSI) --- hyperspectral target detection --- hyperspectral reconstruction --- hyperspectral unmixing
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The Special Issue entitled “Remote Sensing in Vessel Detection and Navigation” comprises 15 articles on many topics related to remote sensing with navigational sensors. The sequence of articles included in this Special Issue is in line with the latest scientific trends. The latest developments in science, including artificial intelligence, were used. It can be said that navigation and vessel detection remain important and hot topics, and a lot of work will continue to be done worldwide. New techniques and methods for analyzing and extracting information from navigational sensors and data have been proposed and verified. Some of these will spark further research, and some are already mature and can be considered for industrial implementation and development.
autonomous navigation --- automatic radar plotting aid --- safe objects control --- game theory --- computer simulation --- Sentinel-2 --- multispectral --- temporal offsets --- ship --- aircraft --- velocity --- altitude --- parallax --- jet stream --- Unmanned Surface Vessel (USV) --- multi-Global Navigation Satellite System (GNSS) receiver --- bathymetric measurements --- cross track error (XTE) --- SSL --- six-degrees-of-freedom motion --- motion attitude model --- edge detection --- straight-line fitting --- visual saliency --- vessel detection --- video monitoring --- inland waterway --- real-time detection --- neural network --- target recognition --- HRRP --- residual structure --- loss function --- trajectory tracking --- unmanned surface vehicle --- navigation --- bathymetry --- hydrographic survey --- real-time communication --- maritime situational awareness --- ship detection --- Iridium --- on-board --- image processing --- flight campaign --- position estimation --- ranging mode --- single shore station --- AIS --- bag-of-words mechanism --- machine learning --- image analysis --- ship classification --- marine system --- river monitoring system --- feature extraction --- synthetic aperture radar (SAR) ship detection --- multi-stage rotational region based network (MSR2N) --- rotated anchor generation --- multi-stage rotational detection network (MSRDN) --- convolutional neural network (CNN) --- synthetic aperture radar (SAR) --- multiscale and small ship detection --- complex background --- false alarm --- farbon dioxide peaks --- midwave infrared --- FTIR --- adaptive stochastic resonance (ASR) --- matched intrawell response --- nonlinear filter --- line enhancer --- autonomous underwater vehicles (AUVs) --- target tracking --- group targets --- GLMB --- structure --- formation --- remote sensing
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