Search Results - "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... by Alabi, Tunrayo, Haertel, M., Chiejile, S.

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

Subjects: “…artificial neural network…”
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NIR instruments and prediction methods for rapid access to grain protein content in multiple cereals by 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

Subjects: “…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​ by Goycochea Casas, Gianmarco, Elera Gonzáles, Duberlí Geomar, Baselly Villanueva, Juan Rodrigo, Pereira Fardin, Leonardo, Garcia Leite, Hélio

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

Subjects: “…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... by Kaur, Simardeep, Singh, Naseeb, Dagar, Preety, Kumar, Amit, Jaiswal, Sandeep, Singh, Binay K., Bhardwaj, Rakesh, Chand Rana, Jai, Riar, Amritbir

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

Subjects: “…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 by Carbajal, M., Ramírez, D., Turin, C., Schaeffer, S.M., Konkel, J., Ninanya, J., Rinza, J., De Mendiburu, F., Zorogastua, P., Villaorduña, L., Quiroz, R.

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Data-driven hydrological discharge simulation in the Limpopo River Basin for transboundary water management by Tlhomole, James, Garcia Andarcia, Mariangel, Matheswaran, Karthikeyan, Borgomeo, E.

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

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Drought forecasting using artificial neural networks and time series of drought indices by Morid, S., Smakhtin, Vladimir U., Bagherzadeh, K.

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Forecasting commodity prices using long-short-term memory neural networks by Ly, Racine, Traoré, Fousseini, Dia, Khadim

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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 by Goycochea Casas, Gianmarco, Baselly Villanueva, Juan Rodrigo, Coimbra Limeira, Mathaus Messias, Eleto Torres, Carlos Moreira Miquelino, Garcia Leite, Hélio

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

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

Subjects: “…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 by Lukić, Katarina, Brnčić, Mladen, Ćurko, Natka, Tomašević, Marina, Valinger, Davor., Denoya, Gabriela Inés, Barba, Francisco J., Kovačević Ganić, Karin

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

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

Subjects: “…convolutional neural networks…”
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Machine learning based groundwater prediction in a data-scarce basin of Ghana by 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.

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

Subjects: “…neural networks…”
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