Applications of Remote Image Capture System in Agriculture
Remote image capture systems are a key element in efficient and sustainable agriculture nowadays. They are increasingly being used to obtain information of interest from the crops, the soil and the environment. It includes different types of capturing devices: from satellites and drones, to in-field...
محفوظ في:
| التنسيق: | Online |
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| اللغة: | الإنجليزية |
| منشور في: |
MDPI - Multidisciplinary Digital Publishing Institute
2021
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| الموضوعات: | |
| الوصول للمادة أونلاين: | ONIX_20210501_9783039438051_1121 |
| الوسوم: |
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| _version_ | 1869523194078035968 |
|---|---|
| collection | Directory of Open Access Books |
| description | Remote image capture systems are a key element in efficient and sustainable agriculture nowadays. They are increasingly being used to obtain information of interest from the crops, the soil and the environment. It includes different types of capturing devices: from satellites and drones, to in-field devices; different types of spectral information, from visible RGB images, to multispectral images; different types of applications; and different types of techniques in the areas of image processing, computer vision, pattern recognition and machine learning. This book covers all these aspects, through a series of chapters that describe specific recent applications of these techniques in interesting problems of agricultural engineering. |
| format | Online |
| id | doab-20.500.12854ir-69375 |
| 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-693752024-04-11T15:10:23Z Applications of Remote Image Capture System in Agriculture Molina Martínez, José Miguel García-Mateos, Ginés SVM budding rate UAV geometric consistency radiometric consistency point clouds ICP reflectance maps vegetation indices Parrot Sequoia artificial intelligence precision agriculture agricultural robot optimization algorithm online operation segmentation coffee leaf rust machine learning deep learning remote sensing Fourth Industrial Revolution Agriculture 4.0 failure strain sandstone digital image correlation Hill–Tsai failure criterion finite element method reference evapotranspiration moisture sensors machine learning regression frequency-domain reflectometry randomizable filtered classifier convolutional neural network U-Net land use banana plantation Panama TR4 aerial photography remote images systematic mapping study agriculture applications total leaf area mixed pixels Cabernet Sauvignon NDVI Normalized Difference Vegetation Index precision viticulture 3D model spatial vision fertirrigation teaching–learning spectrometry Sentinel-2 pasture quality index normalized difference vegetation index normalized difference water index supplementation decision making digital agriculture grape yield estimate berries counting Dilated CNN machine learning algorithms classification performance winter wheat mapping large-scale water stress Prunus avium L. stem water potential low-cost thermography thermal indexes canopy temperature non-water-stressed baselines non-transpiration baseline soil moisture andosols image processing greenhouse automatic tomato harvesting n/a thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology Remote image capture systems are a key element in efficient and sustainable agriculture nowadays. They are increasingly being used to obtain information of interest from the crops, the soil and the environment. It includes different types of capturing devices: from satellites and drones, to in-field devices; different types of spectral information, from visible RGB images, to multispectral images; different types of applications; and different types of techniques in the areas of image processing, computer vision, pattern recognition and machine learning. This book covers all these aspects, through a series of chapters that describe specific recent applications of these techniques in interesting problems of agricultural engineering. 2021-05-01T15:48:11Z 2021-05-01T15:48:11Z 2020 book ONIX_20210501_9783039438051_1121 9783039438051 9783039438068 https://directory.doabooks.org/handle/20.500.12854/69375 eng application/octet-stream Attribution 4.0 International https://mdpi.com/books/pdfview/book/3168 https://mdpi.com/books/pdfview/book/3168 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-03943-806-8 10.3390/books978-3-03943-806-8 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783039438051 9783039438068 310 Basel, Switzerland open access |
| spellingShingle | SVM budding rate UAV geometric consistency radiometric consistency point clouds ICP reflectance maps vegetation indices Parrot Sequoia artificial intelligence precision agriculture agricultural robot optimization algorithm online operation segmentation coffee leaf rust machine learning deep learning remote sensing Fourth Industrial Revolution Agriculture 4.0 failure strain sandstone digital image correlation Hill–Tsai failure criterion finite element method reference evapotranspiration moisture sensors machine learning regression frequency-domain reflectometry randomizable filtered classifier convolutional neural network U-Net land use banana plantation Panama TR4 aerial photography remote images systematic mapping study agriculture applications total leaf area mixed pixels Cabernet Sauvignon NDVI Normalized Difference Vegetation Index precision viticulture 3D model spatial vision fertirrigation teaching–learning spectrometry Sentinel-2 pasture quality index normalized difference vegetation index normalized difference water index supplementation decision making digital agriculture grape yield estimate berries counting Dilated CNN machine learning algorithms classification performance winter wheat mapping large-scale water stress Prunus avium L. stem water potential low-cost thermography thermal indexes canopy temperature non-water-stressed baselines non-transpiration baseline soil moisture andosols image processing greenhouse automatic tomato harvesting n/a thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology Applications of Remote Image Capture System in Agriculture |
| title | Applications of Remote Image Capture System in Agriculture |
| title_full | Applications of Remote Image Capture System in Agriculture |
| title_fullStr | Applications of Remote Image Capture System in Agriculture |
| title_full_unstemmed | Applications of Remote Image Capture System in Agriculture |
| title_short | Applications of Remote Image Capture System in Agriculture |
| title_sort | applications of remote image capture system in agriculture |
| topic | SVM budding rate UAV geometric consistency radiometric consistency point clouds ICP reflectance maps vegetation indices Parrot Sequoia artificial intelligence precision agriculture agricultural robot optimization algorithm online operation segmentation coffee leaf rust machine learning deep learning remote sensing Fourth Industrial Revolution Agriculture 4.0 failure strain sandstone digital image correlation Hill–Tsai failure criterion finite element method reference evapotranspiration moisture sensors machine learning regression frequency-domain reflectometry randomizable filtered classifier convolutional neural network U-Net land use banana plantation Panama TR4 aerial photography remote images systematic mapping study agriculture applications total leaf area mixed pixels Cabernet Sauvignon NDVI Normalized Difference Vegetation Index precision viticulture 3D model spatial vision fertirrigation teaching–learning spectrometry Sentinel-2 pasture quality index normalized difference vegetation index normalized difference water index supplementation decision making digital agriculture grape yield estimate berries counting Dilated CNN machine learning algorithms classification performance winter wheat mapping large-scale water stress Prunus avium L. stem water potential low-cost thermography thermal indexes canopy temperature non-water-stressed baselines non-transpiration baseline soil moisture andosols image processing greenhouse automatic tomato harvesting n/a thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology |
| topic_facet | SVM budding rate UAV geometric consistency radiometric consistency point clouds ICP reflectance maps vegetation indices Parrot Sequoia artificial intelligence precision agriculture agricultural robot optimization algorithm online operation segmentation coffee leaf rust machine learning deep learning remote sensing Fourth Industrial Revolution Agriculture 4.0 failure strain sandstone digital image correlation Hill–Tsai failure criterion finite element method reference evapotranspiration moisture sensors machine learning regression frequency-domain reflectometry randomizable filtered classifier convolutional neural network U-Net land use banana plantation Panama TR4 aerial photography remote images systematic mapping study agriculture applications total leaf area mixed pixels Cabernet Sauvignon NDVI Normalized Difference Vegetation Index precision viticulture 3D model spatial vision fertirrigation teaching–learning spectrometry Sentinel-2 pasture quality index normalized difference vegetation index normalized difference water index supplementation decision making digital agriculture grape yield estimate berries counting Dilated CNN machine learning algorithms classification performance winter wheat mapping large-scale water stress Prunus avium L. stem water potential low-cost thermography thermal indexes canopy temperature non-water-stressed baselines non-transpiration baseline soil moisture andosols image processing greenhouse automatic tomato harvesting n/a thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology |
| url | ONIX_20210501_9783039438051_1121 |