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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 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
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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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Geo-Informatics in Resource Management
| Geo-Informatics in Resource Management |
| Autore | Mesas Carrascosa Francisco Javier |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 |
| Descrizione fisica | 1 electronic resource (206 p.) |
| Soggetto topico | Research & information: general |
| Soggetto non controllato |
secondary succession monitoring
Natura 2000 threats tree detection archival photographs spectro-textural classification granulometric analysis GLCM alpine grassland fractional vegetation cover ground survey precision evaluation multi-scale LAI product validation PROSAIL model EBK crop growth period adaptive K-means algorithm heavy industry heat sources NPP-VIIRS active fire data night-time light data spatial autocorrelation spatial pattern spatial relationship natural wetlands changes associated influencing factors mainland China farmland abandonment mapping textural segmentation aerial imagery land use Poznań agent based modeling disaster management resource allocation high severity level first come first serve geographical information system bearing capacity analytic hierarchy process geographical survey of national conditions hotspot analysis topsis algorithm automatic identification system data 21st Century Maritime Silk Road region oil flow analysis maritime oil chokepoint Middle East Respiratory Syndrome seismic parameters GIS seismicity spatial analysis b-value earthquake catalog future scenarios prelude dynamic of land use Spatial Decision Support System, CORINE Land Cover remote sensing geographic information system |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557296603321 |
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Mesas Carrascosa Francisco Javier
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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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