Resultados de búsqueda - "machine"

Gap-filling eddy covariance methane fluxes: Comparison of machine learning model predictions and uncertainties at FLUXNET-CH4 wetlands por Irvin, Jeremy, Zhou, Sharon, McNicol, Gavin, Lu, Fred, Liu, Vincent, Fluet-Chouinard, Etienne, Ouyang, Zutao, Knox, Sara Helen, Lucas-Moffat, Antje, Trotta, Carlo, Papale, Dario, Vitale, Domenico, Mammarella, Ivan, Alekseychik, Pavel, Aurela, Mika, Avati, Anand, Baldocchi, Dennis, Bansal, Sheel, Bohrer, Gil, Campbell, David I., Jiquan Chen, Chu, Housen, Dalmagro, Higo J., Delwiche, Kyle B., Desai, Ankur R., Euskirchen, Eugénie, Feron, Sarah, Goeckede, Mathias, Heimann, Martin, Helbig, Manuel, Helfter, Carole, Hemes, Kyle S., Hirano, Takashi, Iwata, Hiroki, Jurasinski, Gerald, Kalhori, Aram, Kondrich, Andrew, Lai, Derrick Y.F., Lohila, Annalea, Malhotra, Avni, Merbold, Lutz, Mitra, Bhaskar, Ng, Andrew, Nilsson, Mats B., Noormets, Asko, Peichl, Matthias, Rey Sanchez, A. Camilo, Richardson, Andrew D., Runkle, Benjamin R.K., Schäfer, Karina V.R., Sonnentag, Oliver, Stuart-Haëntjens, Ellen, Sturtevant, Cove, Ueyama, Masahito, Valach, Alex C., Vargas, Rodrigo, Vourlitis, George L., Ward, Eric J., Wong, Guan Xhuan, Zona, Donatella, Alberto, Ma.Carmelita R., Billesbach, David P., Celis, Gerardo, Dolman, Han, Friborg, Thomas, Fuchs, Kathrin, Gogo, Sébastien, Gondwe, Mangaliso J., Goodrich, Jordan P., Gottschalk, Pia, Hörtnagl, Lukas, Jacotot, Adrien, Koebsch, Franziska, Kasak, Kuno, Maier, Regine, Morin, Timothy H., Nemitz, Eiko, Oechel, Walter C., Oikawa, Patricia Y., Ono, Keisuke, Sachs, Torsten, Sakabe, Ayaka, Schuur, Edward A.G., Shortt, Robert, Sullivan, Ryan C., Szutu, Daphne J., Tuittila, Eeva-Stiina, Varlagin, Andrej, Verfaillie, Joseph G., Wille, Christian, Windham-Myers, Lisamarie, Poulter, Benjamin, Jackson, Robert B.

Materias: “…machine…”
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Implementing Cloud Computing for the Digital Mapping of Agricultural Soil Properties from High Resolution UAV Multispectral Imagery por Pizarro, S., Pricope, N.G., Figueroa, D., Carbajal, C., Quispe, M., Vera, J., Alejandro, L., Achallma, L., Gonzalez, I., Salazar, W., Loayza, H., Cruz, J., Arbizu, C.I.

Materias: “…machine learning…”
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Satellite-based Tracking of Agricultural Adaptation Progress in Sub-Saharan Africa por Reymondin, Louis

Materias: “…machine learning…”
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Predicting poverty with vegetation index por Tang, Binh, Liu, Yanyan, Matteson, David S.

Materias: “…machine learning…”
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MusaDeepMosaic: Development of a machine learning genomic mosaic classifier tool. por Vicens, Romain, Cenci, Alberto, Guillaume, Martin, Sardos, Julie, Rouard, Mathieu, Breton, Catherine

Materias: “…machine learning…”
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Factors affecting deep learning model performance in citizen science–based image data collection for agriculture: A case study on coffee crops por Rivera-Palacio, Juan Camilo, Bunn, Christian, Ryo, Masahiro

Materias: “…machine learning…”
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Spatial-temporal coupling of malaria vector habitat suitability and biting probability por Aduvukha, G.R., Abdel-Rahman, E.M., Mutanga, O., Odindi, J., Tonnang, H.E.Z.

Materias: “…machine learning…”
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Development of an automatic fish feeder por Ozigbo, E., Anyadike, C., Gbadebo, F., Okechukwu, R.U.

Materias: “…machine…”
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Predicting climate smart agriculture (CSA) practices using machine learning: A prime exploratory survey por Noma, Freddy, Babu, Suresh Chandra

Materias: “…machine learning…”
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Estimation of soybean grain yield from multispectral high-resolution UAV data with machine learning models in west Africa por Alabi, T.R., Abebe, A.T., Chigeza, G., Fowobaje, K.R.

Materias: “…machine learning…”
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Big data analysis to understanding online songbird trade in Indonesia: What are the most traded species? por Center for International Forestry Research

Materias: “…machine learning…”
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Assessing the performance of the NextGen agroadvisory on wheat yields in Ethiopia por Liben, Feyera, Abera, Wuletawu, Ebrahim, Mohammed, Mesfin, Tewodros, Tesfu, Daniel, Gashaw, Getachew, Bekele, Hawinet, Tilaye, Asmalu, Erkossa, Teklu, Ayele, Kebede, Adimassu, Zenebe, Tamene, Lulseged D.

Materias: “…machine learning…”
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Digital soil mapping using machine learning model for Kapiti in Kenya por Paliwal, Ambica

Materias: “…machine learning…”
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Machine learning- based gridded soil mapping for Kapiti research station and wildlife conservancy, Kenya por Paliwal, Ambica, Cherotich, Fredah, Leitner, Sonja, Pearce, F., Rufino, M., Quinton, J., Dhulipala, Ram, Salavati, M., Gluecks, Ilona V., Whitbread, Anthony M.

Materias: “…machine learning…”
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Discriminating Robusta coffee (Coffea canephora) cropping systems using leaf-level hyperspectral data por Kebede, G., Mudereri, B.T., Abdel-Rahman, E.M., Mutanga, O., Landmann, T., Odindi, J., Motisi, N., Pinard, F., Tonnang, H.E.Z.

Materias: “…machine learning…”
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Detecting cumulative effects of inputs within the flexible production function framework through LASSO shrinkage estimation: Implications for potassium fertilizer use in India por Takeshima, Hiroyuki, Kishore, Avinash

Materias: “…machine learning…”
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Foodgravity: understand food flows using classic gravity model and explainable artificial intelligence techniques por Dusabe, B.

Materias: “…machine learning…”
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Demand intelligence: an extended descriptor report for sub-indicators por Sartas, M., Konlambigue, M.

Materias: “…machine learning…”
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Redes neuronales para la identificación de enfermedades en el cultivo de tomate (Solanum lycopersicum L.) en Honduras por Erazo V., Jorge D., Uema H., Ken S.

Materias: “…Machine Learning…”
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Modelling agricultural drought: a review of latest advances in big data technologies por Houmma, I.H., El Mansouri, L., Gadal, S., Garba, M., Hadria, R.

Materias: “…machine learning…”
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