Remote Sensing for Target Object Detection and Identification
Target object detection and identification are among the primary uses for a remote sensing system. This is crucial in several fields, including environmental and urban monitoring, hazard and disaster management, and defense and military. In recent years, these analyses have used the tremendous amoun...
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| Главные авторы: | , , |
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| Формат: | Online |
| Язык: | английский |
| Опубликовано: |
MDPI - Multidisciplinary Digital Publishing Institute
2021
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| Предметы: | |
| Online-ссылка: | 44793 |
| Метки: |
Нет меток, Требуется 1-ая метка записи!
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| _version_ | 1869524045585711104 |
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| author | Ziemann, Amanda Vivone, Gemine Addesso, Paolo |
| author_browse | Addesso, Paolo Vivone, Gemine Ziemann, Amanda |
| author_facet | Ziemann, Amanda Vivone, Gemine Addesso, Paolo |
| author_sort | Ziemann, Amanda |
| collection | Directory of Open Access Books |
| description | Target object detection and identification are among the primary uses for a remote sensing system. This is crucial in several fields, including environmental and urban monitoring, hazard and disaster management, and defense and military. In recent years, these analyses have used the tremendous amount of data acquired by sensors mounted on satellite, airborne, and unmanned aerial vehicle (UAV) platforms. This book promotes papers exploiting different remote sensing data for target object detection and identification, such as synthetic aperture radar (SAR) imaging and multispectral and hyperspectral imaging. Several cutting-edge contributions, which provide examples of how to select of a technology or another depending on the specific application, will be detailed. |
| format | Online |
| id | doab-20.500.12854ir-58169 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2021 |
| publishDateRange | 2021 |
| publishDateSort | 2021 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-581692024-04-09T11:42:20Z Remote Sensing for Target Object Detection and Identification Ziemann, Amanda Vivone, Gemine Addesso, Paolo G1-922 Q1-390 satellite videos nonconvex tensor robust principle component analysis infrared phase unwrapping non-independent and identical distribution (non-i.i.d.) mixture of Gaussians dictionary construction Color Markov Chain convolutional neural networks ground-based detection hazard prevention ADMM observability pixel-tracking multi-scale pyramidal features thermal infrared target tracking visible component mixture model hyperspectral imagery flux density particle filter framework processor detecting distance rivers water-flow elevation estimation non-convex optimization convolutional neural networks (CNNs) infrared small-faint target detection target detection infrared imaging synthetic aperture radar (SAR) low-rank representation local prior analysis remote sensing images hardware architecture remote sensing image unsupervised saliency model variational Bayesian SAR hyperspectral anomaly detection infrared small target detection object detection partial sum of the tensor nuclear norm superpixel segmentation multi-model deep learning mask sparse representation oil tank detection tiny and dim target detection HSI reconstruction part-based semantic features region proposals unmanned aerial vehicle object matching hidden danger identification remote sensing imagery target identification Lp-norm constraint low rank sparse decomposition bottom-up and top-down contextual information multi-scale strategies sparse coding very-high-resolution (VHR) remote sensing imagery vehicle detection alternating direction method of multipliers adaptive weighting flood hazard tower failure earth entry vehicle thema EDItEUR::R Earth Sciences, Geography, Environment, Planning::RG Geography Target object detection and identification are among the primary uses for a remote sensing system. This is crucial in several fields, including environmental and urban monitoring, hazard and disaster management, and defense and military. In recent years, these analyses have used the tremendous amount of data acquired by sensors mounted on satellite, airborne, and unmanned aerial vehicle (UAV) platforms. This book promotes papers exploiting different remote sensing data for target object detection and identification, such as synthetic aperture radar (SAR) imaging and multispectral and hyperspectral imaging. Several cutting-edge contributions, which provide examples of how to select of a technology or another depending on the specific application, will be detailed. 2021-02-12T01:47:32Z 2021-02-12T01:47:32Z 2020-04-07 23:07:09 2020 book 44793 9783039283330 9783039283323 https://directory.doabooks.org/handle/20.500.12854/58169 eng application/octet-stream Attribution-NonCommercial-NoDerivatives 4.0 International https://mdpi.com/books/pdfview/book/2070 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-03928-333-0 10.3390/books978-3-03928-333-0 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783039283330 9783039283323 336 open access |
| spellingShingle | G1-922 Q1-390 satellite videos nonconvex tensor robust principle component analysis infrared phase unwrapping non-independent and identical distribution (non-i.i.d.) mixture of Gaussians dictionary construction Color Markov Chain convolutional neural networks ground-based detection hazard prevention ADMM observability pixel-tracking multi-scale pyramidal features thermal infrared target tracking visible component mixture model hyperspectral imagery flux density particle filter framework processor detecting distance rivers water-flow elevation estimation non-convex optimization convolutional neural networks (CNNs) infrared small-faint target detection target detection infrared imaging synthetic aperture radar (SAR) low-rank representation local prior analysis remote sensing images hardware architecture remote sensing image unsupervised saliency model variational Bayesian SAR hyperspectral anomaly detection infrared small target detection object detection partial sum of the tensor nuclear norm superpixel segmentation multi-model deep learning mask sparse representation oil tank detection tiny and dim target detection HSI reconstruction part-based semantic features region proposals unmanned aerial vehicle object matching hidden danger identification remote sensing imagery target identification Lp-norm constraint low rank sparse decomposition bottom-up and top-down contextual information multi-scale strategies sparse coding very-high-resolution (VHR) remote sensing imagery vehicle detection alternating direction method of multipliers adaptive weighting flood hazard tower failure earth entry vehicle thema EDItEUR::R Earth Sciences, Geography, Environment, Planning::RG Geography Ziemann, Amanda Vivone, Gemine Addesso, Paolo Remote Sensing for Target Object Detection and Identification |
| title | Remote Sensing for Target Object Detection and Identification |
| title_full | Remote Sensing for Target Object Detection and Identification |
| title_fullStr | Remote Sensing for Target Object Detection and Identification |
| title_full_unstemmed | Remote Sensing for Target Object Detection and Identification |
| title_short | Remote Sensing for Target Object Detection and Identification |
| title_sort | remote sensing for target object detection and identification |
| topic | G1-922 Q1-390 satellite videos nonconvex tensor robust principle component analysis infrared phase unwrapping non-independent and identical distribution (non-i.i.d.) mixture of Gaussians dictionary construction Color Markov Chain convolutional neural networks ground-based detection hazard prevention ADMM observability pixel-tracking multi-scale pyramidal features thermal infrared target tracking visible component mixture model hyperspectral imagery flux density particle filter framework processor detecting distance rivers water-flow elevation estimation non-convex optimization convolutional neural networks (CNNs) infrared small-faint target detection target detection infrared imaging synthetic aperture radar (SAR) low-rank representation local prior analysis remote sensing images hardware architecture remote sensing image unsupervised saliency model variational Bayesian SAR hyperspectral anomaly detection infrared small target detection object detection partial sum of the tensor nuclear norm superpixel segmentation multi-model deep learning mask sparse representation oil tank detection tiny and dim target detection HSI reconstruction part-based semantic features region proposals unmanned aerial vehicle object matching hidden danger identification remote sensing imagery target identification Lp-norm constraint low rank sparse decomposition bottom-up and top-down contextual information multi-scale strategies sparse coding very-high-resolution (VHR) remote sensing imagery vehicle detection alternating direction method of multipliers adaptive weighting flood hazard tower failure earth entry vehicle thema EDItEUR::R Earth Sciences, Geography, Environment, Planning::RG Geography |
| topic_facet | G1-922 Q1-390 satellite videos nonconvex tensor robust principle component analysis infrared phase unwrapping non-independent and identical distribution (non-i.i.d.) mixture of Gaussians dictionary construction Color Markov Chain convolutional neural networks ground-based detection hazard prevention ADMM observability pixel-tracking multi-scale pyramidal features thermal infrared target tracking visible component mixture model hyperspectral imagery flux density particle filter framework processor detecting distance rivers water-flow elevation estimation non-convex optimization convolutional neural networks (CNNs) infrared small-faint target detection target detection infrared imaging synthetic aperture radar (SAR) low-rank representation local prior analysis remote sensing images hardware architecture remote sensing image unsupervised saliency model variational Bayesian SAR hyperspectral anomaly detection infrared small target detection object detection partial sum of the tensor nuclear norm superpixel segmentation multi-model deep learning mask sparse representation oil tank detection tiny and dim target detection HSI reconstruction part-based semantic features region proposals unmanned aerial vehicle object matching hidden danger identification remote sensing imagery target identification Lp-norm constraint low rank sparse decomposition bottom-up and top-down contextual information multi-scale strategies sparse coding very-high-resolution (VHR) remote sensing imagery vehicle detection alternating direction method of multipliers adaptive weighting flood hazard tower failure earth entry vehicle thema EDItEUR::R Earth Sciences, Geography, Environment, Planning::RG Geography |
| url | 44793 |
| work_keys_str_mv | AT ziemannamanda remotesensingfortargetobjectdetectionandidentification AT vivonegemine remotesensingfortargetobjectdetectionandidentification AT addessopaolo remotesensingfortargetobjectdetectionandidentification |