Artificial Neural Networks in Agriculture

Modern agriculture needs to have high production efficiency combined with a high quality of obtained products. This applies to both crop and livestock production. To meet these requirements, advanced methods of data analysis are more and more frequently used, including those derived from artificial...

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Bibliographic Details
Format:	Online
Language:	English
Published:	MDPI - Multidisciplinary Digital Publishing Institute 2022
Subjects:	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 thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general thema EDItEUR::P Mathematics and Science::PS Biology, life sciences thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes
Online Access:	ONIX_20220111_9783036515809_336
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ONIX_20220111_9783036515809_336

Artificial Neural Networks in Agriculture

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