Emerging Sensor Technology in Agriculture |
Autore | Fuentes Sigfredo |
Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 |
Descrizione fisica | 1 electronic resource (240 p.) |
Soggetto topico |
Research & information: general
Geography |
Soggetto non controllato |
apple orchards
modeling and simulation unmanned aerial vehicles fruit ripeness ethylene gas detection 3D crop modeling remote sensing on-ground sensing depth images parameter acquisition capacitor sensor deposit mass pesticide droplets formulations ionization CFD airflow field test monitoring method spectral sensor crop growth computer vision deep learning image processing pose estimation animal detection precision livestock Citrus sinensis L. Osbeck mechanical harvesting acceleration sensor vibration time logistic regression adaptive thresholding fruit detection parameter tuning phenotype phenotyping phenomics Triticum aestivum water deficit stress infrared leaf area index cocoa beans volatile compounds artificial neural networks VitiCanopy app bushfires infrared thermography near-infrared spectroscopy smoke taint artificial intelligence Kinect sensor RGB RGB-D image segmentation colour thresholding bunch area bunch volume point cloud mesh surface reconstruction image analysis cluster morphology machine learning non-invasive sensing technologies proximal sensing precision viticulture partial least square support vector machine Gaussian processes soybean pigeon pea guar tepary bean |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNINA-9910557295003321 |
Fuentes Sigfredo | ||
Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|
Implementation of Artificial Intelligence in Food Science, Food Quality, and Consumer Preference Assessment |
Autore | Fuentes Sigfredo |
Pubbl/distr/stampa | Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
Descrizione fisica | 1 electronic resource (114 p.) |
Soggetto topico |
Research & information: general
Biology, life sciences Technology, engineering, agriculture |
Soggetto non controllato |
sensory
physicochemical measurements artificial neural networks near infra-red spectroscopy wine quality machine learning modeling weather consumer acceptance prediction data fusion emotion recognition facial expression recognition galvanic skin response machine learning neural networks sensory analysis avocado cultivars preference mapping sensory evaluation sensory descriptive analysis consumer science unifloral honeys botanical origin physicochemical parameters classification natural language processing deep learning sensory science flavor lexicon long short-term memory |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNINA-9910566478503321 |
Fuentes Sigfredo | ||
Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|
Implementation of Sensors and Artificial Intelligence for Environmental Hazards Assessment in Urban, Agriculture and Forestry Systems / / Sigfredo Fuentes, [and three others] |
Autore | Fuentes Sigfredo |
Pubbl/distr/stampa | Basel, Switzerland : , : MDPI - Multidisciplinary Digital Publishing Institute, , 2022 |
Descrizione fisica | 1 online resource (206 pages) |
Disciplina | 006.3 |
Soggetto topico |
Artificial Intelligence
Sensor networks Agriculture Forests and forestry |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNINA-9910674031003321 |
Fuentes Sigfredo | ||
Basel, Switzerland : , : MDPI - Multidisciplinary Digital Publishing Institute, , 2022 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
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