Search Results - "Machining."

Gap-filling eddy covariance methane fluxes: Comparison of machine learning model predictions and uncertainties at FLUXNET-CH4 wetlands by 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.

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Implementing Cloud Computing for the Digital Mapping of Agricultural Soil Properties from High Resolution UAV Multispectral Imagery by 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.

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Satellite-based Tracking of Agricultural Adaptation Progress in Sub-Saharan Africa by Reymondin, Louis

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Predicting poverty with vegetation index by Tang, Binh, Liu, Yanyan, Matteson, David S.

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

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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 by Rivera-Palacio, Juan Camilo, Bunn, Christian, Ryo, Masahiro

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Spatial-temporal coupling of malaria vector habitat suitability and biting probability by Aduvukha, G.R., Abdel-Rahman, E.M., Mutanga, O., Odindi, J., Tonnang, H.E.Z.

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Development of an automatic fish feeder by Ozigbo, E., Anyadike, C., Gbadebo, F., Okechukwu, R.U.

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Predicting climate smart agriculture (CSA) practices using machine learning: A prime exploratory survey by Noma, Freddy, Babu, Suresh Chandra

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

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Big data analysis to understanding online songbird trade in Indonesia: What are the most traded species? by Center for International Forestry Research

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Assessing the performance of the NextGen agroadvisory on wheat yields in Ethiopia by 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.

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Digital soil mapping using machine learning model for Kapiti in Kenya by Paliwal, Ambica

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

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

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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 by Takeshima, Hiroyuki, Kishore, Avinash

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Foodgravity: understand food flows using classic gravity model and explainable artificial intelligence techniques by Dusabe, B.

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Demand intelligence: an extended descriptor report for sub-indicators by Sartas, M., Konlambigue, M.

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Redes neuronales para la identificación de enfermedades en el cultivo de tomate (Solanum lycopersicum L.) en Honduras by Erazo V., Jorge D., Uema H., Ken S.

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Modelling agricultural drought: a review of latest advances in big data technologies by Houmma, I.H., El Mansouri, L., Gadal, S., Garba, M., Hadria, R.

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