Search Results - "MACHINE LEARNING"

Tolerance to spittlebugs (Aeneolamia varia) in Urochloa spp. and Megathyrsus maximus grasses: A dataset for plant damage phenotyping by Ruiz-Hurtado, Andres Felipe, Espitia-Buitrago, Paula, Hernández, Luis Miguel, Jauregui, Rosa N., Cardoso, Juan Andres

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A global spectral library to characterize the world’s soil by Viscarra Rossel, Raphael A., Behrens, T, Ben-Dor, E., Brown, D.J., Demattê, JAM, Shepherd, Keith D., Shi, Z, Stenberg, B, Stevens, A, Adamchuk, V, Aïchik, H, Barthèsl, BG, Bartholomeus, H.M., Bayer, AD, Bernoux, Martial, Böttchero, K, Brodský, L, Du, CW, Chappell, A, Fouad, Y, Genot, V, Gómez, C., Grunwald, S., Gubler, A, Hedley, CB, Knadel, M, Morrás, HJM, Nocita, M, Ramírez Lopez, L., Roudier, P., Rufasto Campos, EM, Sanborn, P, Sellitto, VM, Sudduth, KA, Rawlins, BG, Walter, C, Winowiecki, Leigh Ann, Hong, SY, Ji, W

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Relevant loci for milk production in dairy cattle, obtained by machine learning algorithms by Raschia, Maria Agustina, Ríos, Pablo J., Maizon, Daniel Omar, Demitrio, Daniel Arturo, Poli, Mario Andres

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Detection of banana plants and their major diseases through aerial images and machine learning methods: A case study in DR Congo and Republic of Benin by Gómez Selvaraj, Michael, Vergara, Alejandro, Montenegro, Frank, Alonso Ruiz, Henry, Safari, Nancy, Raymaekers, Dries, Ocimati, Walter, Ntamwira, Jules Bagula, Tits, Laurent, Omondi, Bonaventure Aman Oduor, Blomme, Guy

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Innovative use of satellite data from remote sensing and supervised learning to reduce the impact of drought on crop production by CGIAR Research Program on Wheat

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Predicting optical water quality indicators from remote sensing using machine learning algorithms in tropical highlands of Ethiopia by Leggesse, E.S., Zimale, Fasikaw A., Sultan, D., Enku, T., Srinivasan, R., Tilahun, Seifu A.

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ICTforAg 2024: Virtual day session. Monitoring food security trends in digital spaces: A multi-platform approach to nowcast food insecurity by Carneiro, Bia, Tucci, Giulia, Resce, Giuliano, Johnson, Kiersten, Caravaggio, Nicola

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Identificación de zonas afectadas por sales en el Centro Sur de Córdoba usando Google Earth Engine by Gentili, Nicolás, Bocco, Joaquín, Micheloud, Elizabeth, Videla Mensegue, Horacio Rogelio, Córdoba, Mariano

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Can call detail records provide insights into women's empowerment? A case study from Uganda by Slavchevska, Vanya, Tyszler, Marcelo, Burra, Dharani Dhar, Seymour, Greg, Sementsov, Denys, Lierde, Astrid van, King, Brian

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Machine learning innovations for rapid assessments in wheat and rice systems in South Asia. by CGIAR Research Program on Wheat

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Rift Valley fever (RVF) project on Zooniverse, a citizen science platform that allows registered volunteers to identify animals in landscapes from drone imagery by CGIAR Research Program on Agriculture for Nutrition and Health

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Physics-informed machine learning algorithms for forecasting sediment yield: an analysis of physical consistency, sensitivity, and interpretability by El Bilali, A., Brouziyne, Youssef, Attar, O., Lamane, H., Hadri, A., Taleb, A.

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Transforming Ethiopian agriculture: Validating and scaling site-specific fertilizer recommendations to 72,000+ farmers via digital advisory. by Desta, Lulseged Tamene, Mesfin, Tewodros, Abera, Wuletawu, Degefie, Tibebe, Ebrahim, Mohammed, Tilaye, Asmalu, Chernet, Meklit Tariku, Merga, Feyera, Desalegn, Temesgen, Yitaferu, Birru Woldetsadik

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Predicting Risk of Ammonia Exposure in Broiler Housing: Correlation with Incidence of Health Issues by Barbosa, Leonardo V. S., da-Silva-Lima, Nilsa D., Granja-Barrios, Juliana-de-Souza, de-Moura, Daniella J., Estellés, Fernando, Ramón-Moragues, Adrián, Calvet-Sanz, Salvador, Villagrá, Arantxa

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Ensemble machine learning prediction of drivers affecting rice and wheat yield, greenhouse gas emissions, and yield-scaled emissions in Bangladesh by CGIAR Research Program on Climate Change, Agriculture and Food Security

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Assessing the biophysical factors affecting irrigation performance in rice cultivation using remote sensing derived information by Sawadogo, A., Dossou-Yovo, Elliott Ronald, Kouadio, L., Zwart, Sander J., Traoré, F., Gundogdu, K. S.

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Agricultura digital y servicios agroclimáticos: Modernizando los servicios de extensión en el sector arrocero para mejorar la adaptación al clima by Barrios Perez, Camilo

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A comparison between support vector machine and water Cloud model for estimating crop leaf area index by Hosseini, Mehdi, McNairn, Heather, Mitchell, Scott, Robertson, Laura Dingle, Davidson, Andrew, Ahmadian, Nima, Bhattacharya, Avik, Borg, Erik, Conrad, Christopher, Dabrowska Zielinska, Katarzyna, De Abelleyra, Diego, Gurdak, Radoslaw, Kumar, Vineet, Kussul, Nataliia, Mandal, Dipankar, Rao, Y.S., Saliendra, Nicanor, Shelestov, Andrii, Spengler, Daniel, Veron, Santiago Ramón, Homayouni, Saeid, Becker Reshef, Inbal

Subjects: “…Machine Learning…”
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Yield prediction, pest and disease diagnosis, soil fertility mapping, precision irrigation scheduling, and food quality assessment using machine learning and deep learning algorith... by Ajith, S., Vijayakumar, S., Elakkiya, N.

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Updating high-resolution image dataset for the automatic classification of phenological stage and identification of racemes in Urochloa spp. hybrids with expanded images and annota... by Arrechea-Castillo, Darwin Alexis, Espitia-Buitrago, Paula, Florian-Vargas, David, Estupinan, Ronald David, Velázquez-Hernández, Riquelmer, Ruiz-Hurtado, Andres Felipe, Hernandez, Luis Miguel, Jauregui, Rosa Noemi, Cardoso, Juan Andres

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