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Applications of Remote Image Capture System in Agriculture
| Applications of Remote Image Capture System in Agriculture |
| Autore | Molina Martínez José Miguel |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 |
| Descrizione fisica | 1 electronic resource (310 p.) |
| Soggetto topico | History of engineering & technology |
| Soggetto non controllato |
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 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557895803321 |
Molina Martínez José Miguel
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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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Novel Techniques to Measure the Sensory, Emotional, and Physiological (Biometric) Responses of Consumers toward Foods and Packaging
| Novel Techniques to Measure the Sensory, Emotional, and Physiological (Biometric) Responses of Consumers toward Foods and Packaging |
| Autore | Torrico Damir |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 electronic resource (180 p.) |
| Soggetto topico | Psychology |
| Soggetto non controllato |
virtual reality
acceptability Cabernet Sauvignon wine context emotions immersive environments chocolate products hordenine happiness beer consumption sensory analysis beer styles entomophagy neophobia alternative protein source emojis EsSense profile® facial expressions purchase intention energy drinks beef chocolate biometrics Cochran's Q test ethnic plant conscious unconscious check-all-that-apply linear model correspondence analysis RPPG and PPG heart rate branding familiarity soy sauce food images consumer approach-avoidance Approach-Avoidance Task (AAT) valence arousal wanting implicit measure self-report mobile phone home-use test ecological validity jambalaya online auction |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | Novel Techniques to Measure the Sensory, Emotional, and Physiological |
| Record Nr. | UNINA-9910557331503321 |
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Torrico Damir
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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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