TY - BOOK ID - 146280417 TI - Applications of Remote Image Capture System in Agriculture AU - Molina Martínez, José Miguel AU - García-Mateos, Ginés PY - 2020 PB - Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute DB - UniCat KW - History of engineering & technology KW - SVM KW - budding rate KW - UAV KW - geometric consistency KW - radiometric consistency KW - point clouds KW - ICP KW - reflectance maps KW - vegetation indices KW - Parrot Sequoia KW - artificial intelligence KW - precision agriculture KW - agricultural robot KW - optimization algorithm KW - online operation KW - segmentation KW - coffee leaf rust KW - machine learning KW - deep learning KW - remote sensing KW - Fourth Industrial Revolution KW - Agriculture 4.0 KW - failure strain KW - sandstone KW - digital image correlation KW - Hill-Tsai failure criterion KW - finite element method KW - reference evapotranspiration KW - moisture sensors KW - machine learning regression KW - frequency-domain reflectometry KW - randomizable filtered classifier KW - convolutional neural network KW - U-Net KW - land use KW - banana plantation KW - Panama TR4 KW - aerial photography KW - remote images KW - systematic mapping study KW - agriculture KW - applications KW - total leaf area KW - mixed pixels KW - Cabernet Sauvignon KW - NDVI KW - Normalized Difference Vegetation Index KW - precision viticulture KW - 3D model KW - spatial vision KW - fertirrigation KW - teaching-learning KW - spectrometry KW - Sentinel-2 KW - pasture quality index KW - normalized difference vegetation index KW - normalized difference water index KW - supplementation KW - decision making KW - digital agriculture KW - grape yield estimate KW - berries counting KW - Dilated CNN KW - machine learning algorithms KW - classification performance KW - winter wheat mapping KW - large-scale KW - water stress KW - Prunus avium L. KW - stem water potential KW - low-cost thermography KW - thermal indexes KW - canopy temperature KW - non-water-stressed baselines KW - non-transpiration baseline KW - soil moisture KW - andosols KW - image processing KW - greenhouse KW - automatic tomato harvesting KW - SVM KW - budding rate KW - UAV KW - geometric consistency KW - radiometric consistency KW - point clouds KW - ICP KW - reflectance maps KW - vegetation indices KW - Parrot Sequoia KW - artificial intelligence KW - precision agriculture KW - agricultural robot KW - optimization algorithm KW - online operation KW - segmentation KW - coffee leaf rust KW - machine learning KW - deep learning KW - remote sensing KW - Fourth Industrial Revolution KW - Agriculture 4.0 KW - failure strain KW - sandstone KW - digital image correlation KW - Hill-Tsai failure criterion KW - finite element method KW - reference evapotranspiration KW - moisture sensors KW - machine learning regression KW - frequency-domain reflectometry KW - randomizable filtered classifier KW - convolutional neural network KW - U-Net KW - land use KW - banana plantation KW - Panama TR4 KW - aerial photography KW - remote images KW - systematic mapping study KW - agriculture KW - applications KW - total leaf area KW - mixed pixels KW - Cabernet Sauvignon KW - NDVI KW - Normalized Difference Vegetation Index KW - precision viticulture KW - 3D model KW - spatial vision KW - fertirrigation KW - teaching-learning KW - spectrometry KW - Sentinel-2 KW - pasture quality index KW - normalized difference vegetation index KW - normalized difference water index KW - supplementation KW - decision making KW - digital agriculture KW - grape yield estimate KW - berries counting KW - Dilated CNN KW - machine learning algorithms KW - classification performance KW - winter wheat mapping KW - large-scale KW - water stress KW - Prunus avium L. KW - stem water potential KW - low-cost thermography KW - thermal indexes KW - canopy temperature KW - non-water-stressed baselines KW - non-transpiration baseline KW - soil moisture KW - andosols KW - image processing KW - greenhouse KW - automatic tomato harvesting UR - https://www.unicat.be/uniCat?func=search&query=sysid:146280417 AB - 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. ER -