Resultados de búsqueda - "neural network"

Investigating the use of high resolution multi-spectral satellite imagery for crop mapping in Nigeria crop and landuse classification using WorldView-3 high resolution multispectra... por Alabi, Tunrayo, Haertel, M., Chiejile, S.

Materias: “…neural network…”
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Simulation and prediction of soybean growth and development under field conditions por Zhang, L., Zhang, J., Kyei-Boahen, S., Zhang, M.

Materias: “…artificial neural network…”
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NIR instruments and prediction methods for rapid access to grain protein content in multiple cereals por Chadalavada, K., Anbazhagan, K., Ndour, A., Choudhary, S., Palmer, W., Flynn, J.R., Mallayee, S., Sharada, Pothu, Prasad, Kodukula V.S.V., Varijakshapanicker, Padmakumar, Jones, Christopher S., Kholová, Jana

Materias: “…convolution neural network (cnn)…”
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​​Configuration of the deep neural network hyperparameters for the hypsometric modeling of the Guazuma crinita Mart. in the Peruvian Amazon​ por Goycochea Casas, Gianmarco, Elera Gonzáles, Duberlí Geomar, Baselly Villanueva, Juan Rodrigo, Pereira Fardin, Leonardo, Garcia Leite, Hélio

Materias: “…​Artificial neural network…”
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Estimación del aglomerado urbano del AMBA mediante redes neuronales convolucionales en el período 1980-2020 por Sepulcri, Maria Gabriela, Barrionuevo, Nestor, Waldman, Cynthia Paula

Materias: “…Convolutional Neural Network…”
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Comparative analysis of modified partial least squares regression and hybrid deep learning models for predicting protein content in Perilla (Perilla frutescens L.) seed meal using... por Kaur, Simardeep, Singh, Naseeb, Dagar, Preety, Kumar, Amit, Jaiswal, Sandeep, Singh, Binay K., Bhardwaj, Rakesh, Chand Rana, Jai, Riar, Amritbir

Materias: “…neural networks…”
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Editorial: Deep learning approaches applied to spectral images for plant phenotyping por Polder, Gerrit, Blasco, José, Cen, Haiyan

Materias: “…Deep neural networks…”
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From Rangelands to Cropland, Land-Use Change and its impact on soil organic carbon variables in a Peruvian Andean Highlands: A Machine Learning Modeling approach por Carbajal, M., Ramírez, D., Turin, C., Schaeffer, S.M., Konkel, J., Ninanya, J., Rinza, J., De Mendiburu, F., Zorogastua, P., Villaorduña, L., Quiroz, R.

Materias: “…neural networks…”
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Data-driven hydrological discharge simulation in the Limpopo River Basin for transboundary water management por Tlhomole, James, Garcia Andarcia, Mariangel, Matheswaran, Karthikeyan, Borgomeo, E.

Materias: “…neural networks…”
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Artificial neural network model for forecasting future ainfall scenario of Jharkhand state of India por Verma, H.C., Mishra, Atmaram

Materias: “…neural networks…”
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Drought forecasting using artificial neural networks and time series of drought indices por Morid, S., Smakhtin, Vladimir U., Bagherzadeh, K.

Materias: “…neural networks…”
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Forecasting commodity prices using long-short-term memory neural networks por Ly, Racine, Traoré, Fousseini, Dia, Khadim

Materias: “…neural networks…”
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Classifying the risk of forest loss in the Peruvian amazon rainforest: An alternative approach for sustainable forest management using artificial intelligence por Goycochea Casas, Gianmarco, Baselly Villanueva, Juan Rodrigo, Coimbra Limeira, Mathaus Messias, Eleto Torres, Carlos Moreira Miquelino, Garcia Leite, Hélio

Materias: “…Kohonen neural network…”
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Artificial Neural Networks in Agriculture, the core of artificial intelligence: What, When, and Why por Castillo-Gironés, Salvador, Munera, Sandra, Martinez-Sober, Marcelino, Blasco, José, Cubero, Sergio, Gómez-Sanchis, Juan

Materias: “…Neural networks…”
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An artificial neural network model for simulating streamflow using remote sensing data por Gamage, M.S.D.Nilantha, Agrawal, R., Smakhtin, Vladimir U., Perera, B. J. C.

Materias: “…neural networks…”
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Effects of high power ultrasound treatments on the phenolic, chromatic and aroma composition of young and aged red wine por Lukić, Katarina, Brnčić, Mladen, Ćurko, Natka, Tomašević, Marina, Valinger, Davor., Denoya, Gabriela Inés, Barba, Francisco J., Kovačević Ganić, Karin

Materias: “…Artificial Neural Network…”
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Function approximation and documentation of sampling data using artificial neural networks por Zhang, Wenjun, Barrion, Albert

Materias: “…neural networks…”
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Deep learning for image-based cassava disease detection por Ramcharan, A., Baranowski, K., McCloskey, P., Ahmed, B., Legg, James P., Hughes, D.P.

Materias: “…convolutional neural networks…”
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Machine learning based groundwater prediction in a data-scarce basin of Ghana por Siabi, E. K., Dile, Y. T., Kabo-Bah, A. T., Amo-Boateng, M., Anornu, G. K., Akpoti, Komlavi, Vuu, C., Donkor, P., Mensah, S. K., Incoom, A. B. M., Opoku, E. K., Atta-Darkwa, T.

Materias: “…neural networks…”
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Advancing non-optical water quality monitoring in Lake Tana, Ethiopia: insights from machine learning and remote sensing techniques por Leggesse, E. S., Zimale, F. A., Sultan, D., Enku, T., Tilahun, Seifu A.

Materias: “…neural networks…”
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