Info
- Utilizzare la checkbox di selezione a fianco di ciascun documento per attivare le funzionalità di stampa, invio email, download nei formati disponibili del (i) record.
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 electronic resource (438 p.) |
| Soggetto topico | Research & information: general |
| Soggetto non controllato |
synthetic aperture radar
despeckling multi-scale LSTM sub-pixel high-resolution remote sensing imagery road extraction machine learning DenseUNet scene classification lifting scheme convolution CNN image classification deep features hand-crafted features Sinkhorn loss remote sensing text image matching triplet networks EfficientNets LSTM network convolutional neural network water identification water index semantic segmentation high-resolution remote sensing image pixel-wise classification result correction conditional random field (CRF) satellite object detection neural networks single-shot deep learning global convolution network feature fusion depthwise atrous convolution high-resolution representations ISPRS vaihingen Landsat-8 faster region-based convolutional neural network (FRCNN) single-shot multibox detector (SSD) super-resolution remote sensing imagery edge enhancement satellites open-set domain adaptation adversarial learning min-max entropy pareto ranking SAR Sentinel–1 Open Street Map U–Net desert road infrastructure mapping monitoring deep convolutional networks outline extraction misalignments nearest feature selector hyperspectral image classification two stream residual network Batch Normalization plant disease detection precision agriculture UAV multispectral images orthophotos registration 3D information orthophotos segmentation wildfire detection convolutional neural networks densenet generative adversarial networks CycleGAN data augmentation pavement markings visibility framework urban forests OUDN algorithm object-based high spatial resolution remote sensing Generative Adversarial Networks post-disaster building damage assessment anomaly detection Unmanned Aerial Vehicles (UAV) xBD feature engineering orthophoto unsupervised segmentation |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557747903321 |
Bazi Yakoub
|
||
| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Agricultural Irrigation
| Agricultural Irrigation |
| Autore | Montazar Aliasghar |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2019 |
| Descrizione fisica | 1 electronic resource (172 p.) |
| Soggetto non controllato |
semi-arid regions
greenhouse gas emission model simulation spinach benchmarking leaf mineral composition available water capacity irrigated crops organic production site-specific irrigation infiltration depth pumping plants performance indicator treated wastewater irrigation precision agriculture evaluation of performance total yield row cover irrigation slope gradient farming data optimal irrigation time lettuce production life cycle assessment mulch monthly changes irrigation water use efficiency energy audit crop evapotranspiration irrigation management downy mildew biomass production water application rate tomato fruit yield temperature variations irrigation water regimes salinization net irrigation requirements center-pivot irrigation cover crop climate change adaptation deficit irrigation drip irrigation Mediterranean region principal component analysis global sensitivity analysis |
| ISBN | 3-03921-923-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910367740803321 |
|
Montazar Aliasghar
|
||
| MDPI - Multidisciplinary Digital Publishing Institute, 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
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 electronic resource (242 pages) |
| Soggetto topico |
Research
Biology Technology Engineering Agriculture |
| Soggetto non controllato |
irrigation
groundwater alluvial aquifer water conservation adoption row crops Mississippi Delta precision agriculture Lower Mississippi River Valley clogging drip irrigation emitter hydrocyclone digestate liquid fraction wastewater salinity environments AquaCrop model water productivity scenarios tolerant Colorado River Basin drought irrigation management strategy water deficit optimum water use forage BEARS bushland climate evapotranspiration groundwater management irrigation water management Ogallala aquifer region remote sensing lysimeter ET assessment water-use efficiency analytical formula efficient design application efficiency gravity irrigation solar MajiPump water and crop productivity small-scale irrigation conservation agriculture Ethiopia sensible and latent heat fluxes surface renewal method tea plantation eddy covariance squash partial root drying water use efficiency soil mulch growing seasons gas exchange fruit quality Asparagus officinalis L. cultivars spears yield sandy soil water requirements IWUE autonomous landscape irrigation Hargreaves and Samani evapotranspiration model water conservation smart controller |
| 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 | ||
| ||
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
|
||
| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
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 electronic resource (283 p.) |
| Soggetto topico |
Research & information: general
Biology, life sciences Technology, engineering, agriculture |
| Soggetto non controllato |
artificial neural network (ANN)
Grain weevil identification neural modelling classification winter wheat grain artificial neural network ferulic acid deoxynivalenol nivalenol MLP network sensitivity analysis precision agriculture machine learning similarity metric memory deep learning plant growth dynamic response root zone temperature dynamic model NARX neural networks hydroponics vegetation indices UAV neural network corn plant density corn canopy cover yield prediction CLQ GA-BPNN GPP-driven spectral model rice phenology EBK correlation filter crop yield prediction hybrid feature extraction recursive feature elimination wrapper artificial neural networks big data classification high-throughput phenotyping modeling predicting time series forecasting soybean food production paddy rice mapping dynamic time warping LSTM weakly supervised learning cropland mapping apparent soil electrical conductivity (ECa) magnetic susceptibility (MS) EM38 neural networks Phoenix dactylifera L. Medjool dates image classification convolutional neural networks transfer learning average degree of coverage coverage unevenness coefficient optimization high-resolution imagery oil palm tree CNN Faster-RCNN image identification agroecology weeds yield gap environment health crop models soil and plant nutrition automated harvesting model application for sustainable agriculture remote sensing for agriculture decision supporting systems neural image analysis |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557509803321 |
|
Kujawa Sebastian
|
||
| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
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 electronic resource (189 p.) |
| Soggetto topico |
Technology: general issues
Energy industries & utilities |
| Soggetto non controllato |
automotive
current electric power train electric vehicle embedded systems delay detection distributed systems measurements power train sensor signals time delay estimation unmanned aerial vehicles wireless sensor networks intelligent data processing trajectory planning relevant data extraction data consensus Internet of Things precision agriculture system identification smart building artificial neural network energy efficiency black box modeling educational robotics data acquisition sensors ROS STEM CNN (Convolutional neural networks) deep learning pavement defects residual connection attention gate atrous spatial pyramid pooling intelligent charging demand response linear programming optimization smart parking smart grid ODE Solver OpenCL Parareal parallel/multi-core computing sensing systems heterogenous embedded systems deep sparse auto-encoders medical diagnosis linear model data classification PSO algorithm safety-related system component FPGA-designing logical and power-oriented checkability hidden faults clock signal consumed and dissipated power temperature and current consumption sensors |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557333503321 |
|
Stamatescu Grigore
|
||
| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
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 electronic resource (184 p.) |
| Soggetto topico |
Research & information: general
Biology, life sciences Forestry & related industries |
| Soggetto non controllato |
unmanned aerial vehicles
seedling detection forest regeneration reforestation establishment survey machine learning multispectral classification UAV photogrammetry forest modeling ancient trees measurement tree age prediction Mauritia flexuosa semantic segmentation end-to-end learning convolutional neural network forest inventory Unmanned Aerial Systems (UAS) structure from motion (SfM) Unmanned Aerial Vehicles (UAV) Photogrammetry Thematic Mapping Accuracy Assessment Reference Data Forest Sampling Remote Sensing Robinia pseudoacacia L. reproduction spreading short rotation coppice unmanned aerial system (UAS) object-based image analysis (OBIA) convolutional neural network (CNN) juniper woodlands ecohydrology remote sensing unmanned aerial systems central Oregon rangelands seedling stand inventorying photogrammetric point clouds hyperspectral imagery leaf-off leaf-on UAV multispectral image forest fire burn severity classification precision agriculture biomass evaluation image processing Castanea sativa unmanned aerial vehicles (UAV) precision forestry forestry applications RGB imagery |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | Forestry Applications of Unmanned Aerial Vehicles |
| Record Nr. | UNINA-9910557112103321 |
|
Matese Alessandro
|
||
| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
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 electronic resource (266 p.) |
| Soggetto topico |
Research & information: general
Environmental economics |
| Soggetto non controllato |
hyperspectral LiDAR
Red Edge AOTF vegetation parameters leaf chlorophyll content DLARI MDATT adaxial abaxial spectral reflectance peanut field spectroscopy hyperspectral heavy metals grapevine PLS SVM MLR multi-angle observation hyperspectral remote sensing BRDF vegetation classification object-oriented segmentation spectroscopy artificial intelligence proximal sensing data precision agriculture spectra vegetation plant classification discrimination feature selection waveband selection support vector machine random forest Natura 2000 invasive species expansive species biodiversity proximal sensor macronutrient micronutrient remote sensing hyperspectral imaging platforms and sensors analytical methods crop properties soil characteristics classification of agricultural features canopy spectra chlorophyll content continuous wavelet transform (CWT) correlation coefficient partial least square regression (PLSR) reproducibility replicability partial least squares Ethiopia Eragrostis tef hyperspectral remote sensing for soil and crops in agriculture hyperspectral imaging for vegetation plant traits high-resolution spectroscopy for agricultural soils and vegetation hyperspectral databases for agricultural soils and vegetation hyperspectral data as input for modelling soil, crop, and vegetation product validation new hyperspectral technologies future hyperspectral missions |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557691803321 |
|
Pascucci Simone
|
||
| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Mobile Mapping Technologies
| Mobile Mapping Technologies |
| Autore | Chiang Kai-Wei |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2019 |
| Descrizione fisica | 1 electronic resource (334 p.) |
| Soggetto non controllato |
LRF
smartphone unmanned vehicle sensor fusion 2D laser scanner semantic enrichment Vitis vinifera indoor scenes terrestrial laser scanning vine size quadric fitting multi-group-step L-M optimization grammar MLS indoor topological localization trajectory fusion second order hidden Markov model room type tagging fingerprinting restoration laser scanning map management Lidar localization system point clouds binary vocabulary self-calibration 3D processing cultural heritage encoder category matching indoor mapping convolutional neural network (CNN) tunnel cross section visual positioning enhanced RANSAC segmentation-based feature extraction image retrieval handheld crowdsourcing trajectory visual landmark sequence indoor localization mobile mapping rapid relocation sensors configurations precision agriculture 3D digitalization mobile laser scanning robust statistical analysis plant vigor motion estimation visual simultaneous localization and mapping dynamic environment Bayesian inference automated database construction portable mobile mapping system SLAM small-scale vocabulary ORB-SLAM2 LiDAR IMMS point cloud optical sensors tunnel central axis constrained nonlinear least-squares problem 3D point clouds wearable mobile laser system geometric features 2D laser range-finder RGB-D camera OctoMap |
| ISBN | 3-03928-019-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910367736903321 |
|
Chiang Kai-Wei
|
||
| MDPI - Multidisciplinary Digital Publishing Institute, 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Optimizing Plant Water Use Efficiency for a Sustainable Environment
| Optimizing Plant Water Use Efficiency for a Sustainable Environment |
| Autore | Garcia Tejero Ivan Francisco |
| Pubbl/distr/stampa | Basel, : MDPI Books, 2022 |
| Descrizione fisica | 1 electronic resource (366 p.) |
| Soggetto topico |
Research & information: general
Biology, life sciences Technology, engineering, agriculture |
| Soggetto non controllato |
fruit size
Manzanilla olive regulated deficit irrigation water potential water relation leaf area Manihot esculenta photosynthesis tuber water status antioxidant capacity bioactive compounds growth hydroxycinnamic acids hydroponics preformed plastic mulch film crop water productivity biodegradation crop productivity spray-on mulch water use efficiency almond cultivars crop physiological response irrigation water productivity nut yield drip irrigation silicon mineral nutrients oxidative stress osmolytes yield Zea mays ERP GIS internet of things precision agriculture quality environment water software platform web application crop coefficient drought stress evapotranspiration maize water productivity Prunus dulcis Vairo water stress sustained deficit irrigation quality markers leaf greenness index root morphology almond quality sustainability marketability semiarid Mediterranean environment root components yield components fruit quality deficit irrigation leaf area index harvest index photosynthetic rate transpiration rate greenhouse in vitro culture apple cherries midday stem water potential sap flow stomatal conductance FDR probes and daily fraction of intercepted photosynthetically active radiation abiotic stress Linum album Ky. ex Boiss morphological properties phenology pigments diversity root length density root weight density root-shoot relationships benefit-cost ratio nitrogen root growth tomato water saving Jerusalem artichoke mineral fertilization irrigation diseases fungi crop suitability remote sensing ALES-Arid SEBAL landsat crop-water requirements smart farming crop-production functions food quality crop physiological response to drought scenarios |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910595078203321 |
|
Garcia Tejero Ivan Francisco
|
||
| Basel, : MDPI Books, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
