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Advanced Deep Learning Strategies for the Analysis of Remote Sensing Images
| Advanced Deep Learning Strategies for the Analysis of Remote Sensing Images |
| Autore | Bazi Yakoub |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 online resource (438 p.) |
| Soggetto topico | Research and information: general |
| Soggetto non controllato |
3D information
adversarial learning anomaly detection Batch Normalization building damage assessment CNN conditional random field (CRF) convolution convolutional neural network convolutional neural networks CycleGAN data augmentation deep convolutional networks deep features deep learning densenet DenseUNet depthwise atrous convolution desert despeckling edge enhancement EfficientNets faster region-based convolutional neural network (FRCNN) feature engineering feature fusion framework generative adversarial networks Generative Adversarial Networks global convolution network hand-crafted features high spatial resolution remote sensing high-resolution remote sensing image high-resolution remote sensing imagery high-resolution representations hyperspectral image classification image classification infrastructure ISPRS vaihingen Landsat-8 lifting scheme LSTM LSTM network machine learning mapping min-max entropy misalignments monitoring multi-scale nearest feature selector neural networks object detection object-based Open Street Map open-set domain adaptation orthophoto orthophotos registration orthophotos segmentation OUDN algorithm outline extraction pareto ranking pavement markings pixel-wise classification plant disease detection post-disaster precision agriculture remote sensing remote sensing imagery result correction road road extraction SAR satellite satellites scene classification semantic segmentation Sentinel-1 single-shot single-shot multibox detector (SSD) Sinkhorn loss sub-pixel super-resolution synthetic aperture radar text image matching triplet networks two stream residual network U-Net UAV multispectral images Unmanned Aerial Vehicles (UAV) unsupervised segmentation urban forests visibility water identification water index wildfire detection xBD |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557747903321 |
Bazi Yakoub
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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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Agricultural Irrigation
| Agricultural Irrigation |
| Autore | Montazar Aliasghar |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2019 |
| Descrizione fisica | 1 online resource (172 p.) |
| Soggetto topico | Biology, life sciences |
| Soggetto non controllato |
available water capacity
benchmarking biomass production center-pivot irrigation climate change adaptation cover crop crop evapotranspiration deficit irrigation downy mildew drip irrigation energy audit evaluation of performance farming data global sensitivity analysis greenhouse gas emission infiltration depth irrigated crops irrigation irrigation management irrigation water regimes irrigation water use efficiency leaf mineral composition lettuce production life cycle assessment Mediterranean region model simulation monthly changes mulch net irrigation requirements optimal irrigation time organic production performance indicator precision agriculture principal component analysis pumping plants row cover salinization semi-arid regions site-specific irrigation slope gradient spinach temperature variations tomato fruit yield total yield treated wastewater irrigation water application rate |
| ISBN | 3-03921-923-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910367740803321 |
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Montazar Aliasghar
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| MDPI - Multidisciplinary Digital Publishing Institute, 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Agricultural Water Conservation: Tools, Strategies, and Practices
| Agricultural Water Conservation: Tools, Strategies, and Practices |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 online resource (242 p.) |
| Soggetto topico |
Biology, life sciences
Research & information: general Technology, engineering, agriculture |
| Soggetto non controllato |
alluvial aquifer
analytical formula application efficiency AquaCrop model Asparagus officinalis L. autonomous landscape irrigation BEARS bushland climate clogging Colorado River Basin conservation agriculture cultivars digestate liquid fraction drip irrigation drought eddy covariance efficient design emitter environments Ethiopia evapotranspiration forage fruit quality gas exchange gravity irrigation groundwater groundwater management growing seasons Hargreaves and Samani evapotranspiration model hydrocyclone irrigation irrigation management strategy irrigation water management IWUE Lower Mississippi River Valley lysimeter ET assessment Mississippi Delta n/a Ogallala aquifer region optimum water use partial root drying precision agriculture remote sensing row crops salinity sandy soil scenarios sensible and latent heat fluxes small-scale irrigation smart controller soil mulch solar MajiPump spears yield squash surface renewal method tea plantation tolerant wastewater water and crop productivity water conservation water conservation adoption water deficit water productivity water requirements water use efficiency water-use efficiency |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | Agricultural Water Conservation |
| Record Nr. | UNINA-9910557482703321 |
| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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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 online resource (310 p.) |
| Soggetto topico | History of engineering and technology |
| Soggetto non controllato |
3D model
aerial photography agricultural robot agriculture Agriculture 4.0 andosols applications artificial intelligence automatic tomato harvesting banana plantation berries counting budding rate Cabernet Sauvignon canopy temperature classification performance coffee leaf rust convolutional neural network decision making deep learning digital agriculture digital image correlation Dilated CNN failure strain fertirrigation finite element method Fourth Industrial Revolution frequency-domain reflectometry geometric consistency grape yield estimate greenhouse Hill-Tsai failure criterion ICP image processing land use large-scale low-cost thermography machine learning machine learning algorithms machine learning regression mixed pixels moisture sensors n/a NDVI non-transpiration baseline non-water-stressed baselines normalized difference vegetation index Normalized Difference Vegetation Index normalized difference water index online operation optimization algorithm Panama TR4 Parrot Sequoia pasture quality index point clouds precision agriculture precision viticulture Prunus avium L. radiometric consistency randomizable filtered classifier reference evapotranspiration reflectance maps remote images remote sensing sandstone segmentation Sentinel-2 soil moisture spatial vision spectrometry stem water potential supplementation SVM systematic mapping study teaching-learning thermal indexes total leaf area U-Net UAV vegetation indices water stress winter wheat mapping |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557895803321 |
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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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Artificial Neural Networks in Agriculture
| Artificial Neural Networks in Agriculture |
| Autore | Kujawa Sebastian |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 online resource (283 p.) |
| Soggetto topico |
Biology, life sciences
Research & information: general Technology, engineering, agriculture |
| Soggetto non controllato |
agroecology
apparent soil electrical conductivity (ECa) artificial neural network artificial neural network (ANN) artificial neural networks automated harvesting average degree of coverage big data classification CLQ CNN convolutional neural networks corn canopy cover corn plant density correlation filter coverage unevenness coefficient crop models crop yield prediction cropland mapping decision supporting systems deep learning deoxynivalenol dynamic model dynamic response dynamic time warping EBK EM38 environment Faster-RCNN ferulic acid food production GA-BPNN GPP-driven spectral model grain Grain weevil identification health high-resolution imagery high-throughput phenotyping hybrid feature extraction hydroponics image classification image identification LSTM machine learning magnetic susceptibility (MS) Medjool dates memory metric MLP network model application for sustainable agriculture modeling NARX neural networks neural image analysis neural modelling classification neural network neural networks nivalenol oil palm tree optimization paddy rice mapping Phoenix dactylifera L. plant growth precision agriculture predicting recursive feature elimination wrapper remote sensing for agriculture rice phenology root zone temperature sensitivity analysis similarity soil and plant nutrition soybean time series forecasting transfer learning UAV vegetation indices weakly supervised learning weeds winter wheat yield gap yield prediction |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557509803321 |
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Kujawa Sebastian
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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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Convergence of Intelligent Data Acquisition and Advanced Computing Systems
| Convergence of Intelligent Data Acquisition and Advanced Computing Systems |
| Autore | Stamatescu Grigore |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 online resource (189 p.) |
| Soggetto topico |
Energy industries & utilities
Technology: general issues |
| Soggetto non controllato |
artificial neural network
atrous spatial pyramid pooling attention gate automotive black box modeling clock signal CNN (Convolutional neural networks) component consumed and dissipated power current data acquisition data classification data consensus deep learning deep sparse auto-encoders delay demand response detection distributed systems educational robotics electric power train electric vehicle embedded systems energy efficiency FPGA-designing heterogenous embedded systems hidden faults intelligent charging intelligent data processing Internet of Things linear model linear programming logical and power-oriented checkability measurements medical diagnosis n/a ODE Solver OpenCL optimization parallel/multi-core computing Parareal pavement defects power train precision agriculture PSO algorithm relevant data extraction residual connection ROS safety-related system sensing systems sensor sensors signals smart building smart grid smart parking STEM system identification temperature and current consumption sensors time delay estimation trajectory planning unmanned aerial vehicles wireless sensor networks |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557333503321 |
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Stamatescu Grigore
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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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Forestry Applications of Unmanned Aerial Vehicles (UAVs) 2019
| Forestry Applications of Unmanned Aerial Vehicles (UAVs) 2019 |
| Autore | Matese Alessandro |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 |
| Descrizione fisica | 1 online resource (184 p.) |
| Soggetto topico |
Biology, life sciences
Forestry & related industries Research & information: general |
| Soggetto non controllato |
Accuracy Assessment
ancient trees measurement biomass evaluation burn severity Castanea sativa central Oregon classification convolutional neural network convolutional neural network (CNN) ecohydrology end-to-end learning establishment survey forest fire forest inventory forest modeling forest regeneration Forest Sampling forestry applications hyperspectral imagery image processing juniper woodlands leaf-off leaf-on machine learning Mauritia flexuosa multispectral classification multispectral image object-based image analysis (OBIA) photogrammetric point clouds Photogrammetry precision agriculture precision forestry rangelands Reference Data reforestation remote sensing Remote Sensing reproduction RGB imagery Robinia pseudoacacia L. seedling detection seedling stand inventorying semantic segmentation short rotation coppice spreading structure from motion (SfM) Thematic Mapping tree age prediction UAV UAV photogrammetry unmanned aerial system (UAS) unmanned aerial systems Unmanned Aerial Systems (UAS) unmanned aerial vehicles unmanned aerial vehicles (UAV) Unmanned Aerial Vehicles (UAV) |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | Forestry Applications of Unmanned Aerial Vehicles |
| Record Nr. | UNINA-9910557112103321 |
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Matese Alessandro
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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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Hyperspectral Remote Sensing of Agriculture and Vegetation
| Hyperspectral Remote Sensing of Agriculture and Vegetation |
| Autore | Pascucci Simone |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 online resource (266 p.) |
| Soggetto topico |
Environmental economics
Research & information: general |
| Soggetto non controllato |
abaxial
adaxial analytical methods AOTF artificial intelligence biodiversity BRDF canopy spectra chlorophyll content classification classification of agricultural features continuous wavelet transform (CWT) correlation coefficient crop properties discrimination DLARI Eragrostis tef Ethiopia expansive species feature selection field spectroscopy future hyperspectral missions grapevine heavy metals high-resolution spectroscopy for agricultural soils and vegetation hyperspectral hyperspectral data as input for modelling soil, crop, and vegetation hyperspectral databases for agricultural soils and vegetation hyperspectral imaging hyperspectral imaging for vegetation hyperspectral LiDAR hyperspectral remote sensing hyperspectral remote sensing for soil and crops in agriculture invasive species leaf chlorophyll content macronutrient MDATT micronutrient MLR multi-angle observation Natura 2000 new hyperspectral technologies object-oriented segmentation partial least square regression (PLSR) partial least squares peanut plant plant traits platforms and sensors PLS precision agriculture product validation proximal sensing data proximal sensor random forest Red Edge remote sensing replicability reproducibility soil characteristics spectra spectral reflectance spectroscopy support vector machine SVM vegetation vegetation classification vegetation parameters waveband selection |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557691803321 |
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Pascucci Simone
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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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Mobile Mapping Technologies
| Mobile Mapping Technologies |
| Autore | Chiang Kai-Wei |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2019 |
| Descrizione fisica | 1 online resource (334 p.) |
| Soggetto topico | History of engineering and technology |
| Soggetto non controllato |
2D laser range-finder
2D laser scanner 3D digitalization 3D point clouds 3D processing automated database construction Bayesian inference binary vocabulary category matching constrained nonlinear least-squares problem convolutional neural network (CNN) crowdsourcing trajectory cultural heritage dynamic environment encoder enhanced RANSAC fingerprinting geometric features grammar handheld image retrieval IMMS indoor localization indoor mapping indoor scenes indoor topological localization laser scanning LiDAR Lidar localization system LRF map management MLS mobile laser scanning mobile mapping motion estimation multi-group-step L-M optimization OctoMap optical sensors ORB-SLAM2 plant vigor point cloud point clouds portable mobile mapping system precision agriculture quadric fitting rapid relocation restoration RGB-D camera robust statistical analysis room type tagging second order hidden Markov model segmentation-based feature extraction self-calibration semantic enrichment sensor fusion sensors configurations SLAM small-scale vocabulary smartphone terrestrial laser scanning trajectory fusion tunnel central axis tunnel cross section unmanned vehicle vine size visual landmark sequence visual positioning visual simultaneous localization and mapping Vitis vinifera wearable mobile laser system |
| ISBN | 3-03928-019-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910367736903321 |
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Chiang Kai-Wei
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| MDPI - Multidisciplinary Digital Publishing Institute, 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Optimizing Plant Water Use Efficiency for a Sustainable Environment
| Optimizing Plant Water Use Efficiency for a Sustainable Environment |
| Autore | Garcia Tejero Ivan Francisco |
| Descrizione fisica | 1 online resource (366 p.) |
| Soggetto topico |
Biology, life sciences
Research & information: general Technology, engineering, agriculture |
| Soggetto non controllato |
abiotic stress
ALES-Arid almond cultivars almond quality antioxidant capacity apple benefit-cost ratio bioactive compounds biodegradation cherries crop coefficient crop physiological response crop physiological response to drought scenarios crop productivity crop suitability crop water productivity crop-production functions crop-water requirements deficit irrigation diseases diversity drip irrigation drought stress environment ERP evapotranspiration FDR probes and daily fraction of intercepted photosynthetically active radiation food quality fruit quality fruit size fungi GIS greenhouse growth harvest index hydroponics hydroxycinnamic acids in vitro culture internet of things irrigation irrigation water productivity Jerusalem artichoke landsat leaf area leaf area index leaf greenness index Linum album Ky. ex Boiss maize Manihot esculenta Manzanilla marketability midday stem water potential mineral fertilization mineral nutrients morphological properties nitrogen nut yield olive osmolytes oxidative stress phenology photosynthesis photosynthetic rate pigments platform precision agriculture preformed plastic mulch film Prunus dulcis quality quality markers regulated deficit irrigation remote sensing root components root growth root length density root morphology root weight density root-shoot relationships sap flow SEBAL semiarid Mediterranean environment silicon smart farming software spray-on mulch stomatal conductance sustainability sustained deficit irrigation tomato transpiration rate tuber Vairo water water potential water productivity water relation water saving water status water stress water use efficiency web application yield yield components Zea mays |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910595078203321 |
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Garcia Tejero Ivan Francisco
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| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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