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2019, ISBN 9783038974123
CARS | obstacle detection | stratification | optical sensor | neural networks | spectral analysis | regression estimator | Kinect | response surface sampling | sensor evaluation | electromagnetic induction | multivariate water quality parameters | mandarin orange | proximity sensing | crop inspection platform | SPA-MLR | object tracking | distributed systems | feature selection | pest | simultaneous measurement | noninvasive detection | texture feature | diseases | soil mapping | genetic algorithms | classification | soil salinity | processing of sensed data | visible and near-infrared reflectance spectroscopy | germination | electrochemical sensors | thermal image | computer vision | ECa-directed soil sampling | handheld | hyperspectral imaging | recognition patterns | salt concentration | clover-grass | diffusion | dielectric dispersion | UAS | random forests | bovine embedded hardware | weed control | soil | case studies | total nitrogen | field crops | thermal imaging | cameras | dry matter composition | vineyard | near-infrared | connected dominating set | water depth sensors | salt tolerance | SS-OCT | wheat | deep convolutional neural networks | striped stem-borer | silage | geostatistics | detection | NIR hyperspectral imaging | soil type classification | water management | preprocessing methods | wireless sensor networks (WSN) | electronic nose | remote sensing image classification | machine learning | precision plant protection | radar | virtual organizations of agents | spatial variability | GF-1 satellite | packing density | data validation and calibration | dataset | Wi-SUN | temperature sensors | plant disease | naked barley | geoinformatics | gas sensor | X-ray fluorescence spectroscopy | vegetable oil | leaf area index | CIE-Lab | photograph-grid method | Vitis vinifera | change of support | WSN distribution algorithms | radiative transfer model | laser-induced breakdown spectroscopy | irrigation | 3D reconstruction | plant phenotyping | quality assessment | energy efficiency | wireless sensor network (WSN) | geo-information | Fusarium | texture features | weeds | discrimination | big data | soil moisture sensors | vine | meat spoilage | land cover | stereo imaging | near infrared | near infrared sensors | vegetation indices | remote sensing | greenhouse | biological sensing | compound sensor | pest management | moisture | plant localization | heavy metal contamination | artificial neural networks | time-series data | scattering | spectral pre-processing | sensor | crop area | moisture content | apparent soil electrical conductivity | data fusion | speckle | spatial data | semi-arid regions | smart irrigation | grapevine breeding | back propagation model | wide field view | partial least squares-discriminant analysis | spiking | area frame sampling | wireless sensor network | energy balance | light-beam | chromium content | fluorescent measurement | agriculture | machine-learning | precision agriculture | deep learning | RGB-D sensor | spectroscopy | hulled barely | dielectric probe | pest scouting | RPAS | water supply network | PLS | rice leaves | Capsicum annuum | spatial-temporal model | drying temperature | boron tolerance | mobile app | ambient intelligence | gradient boosted machines | hyperspectral camera | one-class | laser wavelength | nitrogen | LiDAR | fuzzy logic | dynamic weight | total carbon | chemometrics analysis | rice | landslide | management zones | agricultural land | on-line vis-NIR measurement | real-time processing | event detection | crop monitoring | apple shelf-life | rice field monitoring | wireless sensor | birth sensor | proximal sensor
eBook
2019, ISBN 3038977454
CARS | obstacle detection | stratification | optical sensor | neural networks | spectral analysis | regression estimator | Kinect | response surface sampling | sensor evaluation | electromagnetic induction | multivariate water quality parameters | mandarin orange | proximity sensing | crop inspection platform | SPA-MLR | object tracking | distributed systems | feature selection | pest | simultaneous measurement | noninvasive detection | texture feature | diseases | soil mapping | genetic algorithms | classification | soil salinity | processing of sensed data | visible and near-infrared reflectance spectroscopy | germination | electrochemical sensors | thermal image | computer vision | ECa-directed soil sampling | handheld | hyperspectral imaging | recognition patterns | salt concentration | clover-grass | diffusion | dielectric dispersion | UAS | random forests | bovine embedded hardware | weed control | soil | case studies | total nitrogen | field crops | thermal imaging | cameras | dry matter composition | vineyard | near-infrared | connected dominating set | water depth sensors | salt tolerance | SS-OCT | wheat | deep convolutional neural networks | striped stem-borer | silage | geostatistics | detection | NIR hyperspectral imaging | soil type classification | water management | preprocessing methods | wireless sensor networks (WSN) | electronic nose | remote sensing image classification | machine learning | precision plant protection | radar | virtual organizations of agents | spatial variability | GF-1 satellite | packing density | data validation and calibration | dataset | Wi-SUN | temperature sensors | plant disease | naked barley | geoinformatics | gas sensor | X-ray fluorescence spectroscopy | vegetable oil | leaf area index | CIE-Lab | photograph-grid method | Vitis vinifera | change of support | WSN distribution algorithms | radiative transfer model | laser-induced breakdown spectroscopy | irrigation | 3D reconstruction | plant phenotyping | quality assessment | energy efficiency | wireless sensor network (WSN) | geo-information | Fusarium | texture features | weeds | discrimination | big data | soil moisture sensors | vine | meat spoilage | land cover | stereo imaging | near infrared | near infrared sensors | vegetation indices | remote sensing | greenhouse | biological sensing | compound sensor | pest management | moisture | plant localization | heavy metal contamination | artificial neural networks | time-series data | scattering | spectral pre-processing | sensor | crop area | moisture content | apparent soil electrical conductivity | data fusion | speckle | spatial data | semi-arid regions | smart irrigation | grapevine breeding | back propagation model | wide field view | partial least squares-discriminant analysis | spiking | area frame sampling | wireless sensor network | energy balance | light-beam | chromium content | fluorescent measurement | agriculture | machine-learning | precision agriculture | deep learning | RGB-D sensor | spectroscopy | hulled barely | dielectric probe | pest scouting | RPAS | water supply network | PLS | rice leaves | Capsicum annuum | spatial-temporal model | drying temperature | boron tolerance | mobile app | ambient intelligence | gradient boosted machines | hyperspectral camera | one-class | laser wavelength | nitrogen | LiDAR | fuzzy logic | dynamic weight | total carbon | chemometrics analysis | rice | landslide | management zones | agricultural land | on-line vis-NIR measurement | real-time processing | event detection | crop monitoring | apple shelf-life | rice field monitoring | wireless sensor | birth sensor | proximal sensor
eBook
Journal of the Meteorological Society of Japan, ISSN 0026-1165, 04/2020, Volume 98, Issue 2, pp. 353 - 377
Journal Article