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Smart Sensing Technologies for Agriculture
| Smart Sensing Technologies for Agriculture |
| Autore | Adamchuk Viacheslav I |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 |
| Descrizione fisica | 1 online resource (232 p.) |
| Soggetto topico | History of engineering and technology |
| Soggetto non controllato |
adaptive K-means
apparent electrical conductivity (ECa) autonomous robot body dimensions boundary-line broiler surface temperature extraction cation exchange capacity clay content convolutional neural networks crop protection cutting point detection deep learning droplet characterization elemental composition ellipse fitting feature recognition FFPH germination paper gripper harvesting robot head region locating infrared spectroscopy ion-selective electrode (ISE) Kalman filter Kd-network kinetic stereo imaging laser-induced breakdown spectroscopy law of minimum LIBS livestock lying posture machine vision mapping model predictive control moisture measurement multispectral imaging non-contact measurement on-site detection optical micro-sensors partial least squares (PLS) pH plant detection point cloud precision agriculture precision farming precision weeding principal component analysis (PCA) proximal soil sensing quantile regression quasi-3D inversion algorithm real-time measurement sandy infertile soil segmentation sensor fusion soil soil electrical resistivity soil moisture soil nitrate nitrogen (NO3−-N) soil nutrients soil testing spectroscopy standing posture thermal image processing Three-dimensional mapping transfer learning UAV willow tree X-ray fluorescence yield estimation |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557667303321 |
Adamchuk Viacheslav I
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| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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UAVs for Vegetation Monitoring
| UAVs for Vegetation Monitoring |
| Autore | de Castro Megías Ana |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 online resource (452 p.) |
| Soggetto topico | Research & information: general |
| Soggetto non controllato |
Acacia
agro-environmental measures artificial intelligence artificial neural network banana broad-sense heritability canopy cover canopy height century-old biochar chlorophyll content CIELab classification close remote sensing CNN container-grown contextual spatial domain/resolution convolution neural network cotton root rot crop canopy crop disease crop mapping crop monitoring curve fitting data aggregation deep learning detection performance disease detection disease diagnosis disease monitoring drone drought tolerance eddy covariance (EC) evapotranspiration (ET) Faster RCNN flight altitude forage grass forest Fusarium wilt Glycine max GRAPEX growth model high throughput field phenotyping HSV hyperspectral image analysis image segmentation Inception v2 individual plant segmentation Indonesia inference time land cover least squares support vector machine machine learning maize tassel method comparison MobileNet v2 multiple linear regression multiscale textures multispectral multispectral image multispectral imagery multispectral remote sensing NDVI neural network nitrogen stress nutrient deficiency oil palm olive groves operating parameters ornamental patch-based CNN phenotyping gap plant detection plant nitrogen estimation plant segmentation plant trails plant-by-plant plant-level precision agriculture purple rapeseed leaves random forest red-edge spectra remote sensing remote sensing technique RGB RGB camera RGB imagery semantic segmentation single-plant solar zenith angle southern Spain spatial resolution SSD sUAS support vector machine tassel branch number texture thermal thermal camera time of day transfer learning transpiration tropics Two Source Energy Balance model (TSEB) U-Net UAS UAV UAV digital images UAV hyperspectral UAV remote sensing unmanned aerial vehicle variable importance vegetation cover vegetation ground cover vegetation index vegetation indices VGG16 visual recognition water stress weed detection wheat yellow rust winter wheat biomass |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557661103321 |
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de Castro Megías Ana
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| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||