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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 electronic resource (452 p.) |
| Soggetto topico | Research & information: general |
| Soggetto non controllato |
UAS
UAV vegetation cover multispectral land cover forest Acacia Indonesia tropics vegetation ground cover vegetation indices agro-environmental measures olive groves southern Spain sUAS water stress ornamental container-grown artificial intelligence machine learning deep learning neural network visual recognition precision agriculture canopy cover image analysis crop mapping evapotranspiration (ET) GRAPEX remote sensing Two Source Energy Balance model (TSEB) contextual spatial domain/resolution data aggregation eddy covariance (EC) Fusarium wilt crop disease banana multispectral remote sensing purple rapeseed leaves unmanned aerial vehicle U-Net plant segmentation nitrogen stress Glycine max RGB canopy height close remote sensing growth model curve fitting NDVI solar zenith angle flight altitude time of day operating parameters CNN Faster RCNN SSD Inception v2 patch-based CNN MobileNet v2 detection performance inference time disease detection cotton root rot plant-level single-plant plant-by-plant classification UAV remote sensing crop monitoring RGB imagery multispectral imagery century-old biochar semantic segmentation random forest crop canopy multispectral image chlorophyll content remote sensing technique individual plant segmentation plant detection transfer learning maize tassel tassel branch number convolution neural network VGG16 plant nitrogen estimation vegetation index image segmentation transpiration method comparison oil palm multiple linear regression support vector machine artificial neural network UAV hyperspectral wheat yellow rust disease monitoring texture spatial resolution RGB camera thermal camera drought tolerance forage grass HSV CIELab broad-sense heritability phenotyping gap high throughput field phenotyping UAV digital images winter wheat biomass multiscale textures red-edge spectra least squares support vector machine variable importance drone hyperspectral thermal nutrient deficiency weed detection disease diagnosis plant trails |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557661103321 |
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 | ||
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Ultrasound Elastography
| Ultrasound Elastography |
| Autore | Dietrich Christoph F |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2019 |
| Descrizione fisica | 1 electronic resource (144 p.) |
| Soggetto non controllato |
ultrasonography
elastography anti-HBV therapy pediatric WFUMB measurement variability tendon stiffness pancreas patellar positions point of care ultrasound time of day chronic hepatitis B quantification chronic hepatitis C EFSUMB stiffness liver cirrhosis liver fibrosis computer-aided diagnosis (CAD) guideline liver stiffness Achilles tendon bending energy ultrasound elastography acoustic radiation force impulse tendinopathy texture analysis power spectrum magnetic resonance imaging strain ratio thyroid cancer prior activity direct acting antivirals strain quantification patellar tendon shear wave elastography (SWE) cine-tagging cirrhosis health care shear wave elastography Crohn’s disease contrast enhanced ultrasound HCV core antigen shear modulus therapy ultrasound supersonic shear imaging carcinoma quantitative leg dominance viral hepatitis C strain elastography endoscopic ultrasound (EUS) |
| ISBN | 3-03897-911-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910346685303321 |
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Dietrich Christoph F
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| MDPI - Multidisciplinary Digital Publishing Institute, 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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