Resultados de búsqueda - "Learning."

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

Materias: “…machine learning…”
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Strengthening facilitation competencies in development: processes, challenges and lessons of a learning alliance to develop facilitators for local community engagement por Lefore, Nicole

Materias: “…learning…”
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Análisis colectivo sobre un módulo móvil de producción de huevos de gallinas libres de jaula, como tecnología adecuada para la Agricultura Familiar en la provincia de Buenos Aires,... por Marcozzi, Paula, Liljesthröm, Verónica, Gamietea, Ignacio José

Materias: “…Collective Learning…”
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Identificación de zonas afectadas por sales en el Centro Sur de Córdoba usando Google Earth Engine por Gentili, Nicolás, Bocco, Joaquín, Micheloud, Elizabeth, Videla Mensegue, Horacio Rogelio, Córdoba, Mariano

Materias: “…Machine Learning…”
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Can call detail records provide insights into women's empowerment? A case study from Uganda por Slavchevska, Vanya, Tyszler, Marcelo, Burra, Dharani Dhar, Seymour, Greg, Sementsov, Denys, Lierde, Astrid van, King, Brian

Materias: “…machine learning…”
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Using the learning alliance approach to develop national and sub national policies e.g climate change guidelines for the Ministry of Agriculture, Animal Industry and Fisheries por CGIAR Research Program on Climate Change, Agriculture and Food Security

Materias: “…learning…”
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Evaluation of a water management training program in Tajikistan leads to redesign to target women farmers and informs Feed the Future Learning Agenda(WLE-IWMI) por CGIAR Research Program on Water, Land and Ecosystems

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

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

Materias: “…machine learning…”
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Predicting Risk of Ammonia Exposure in Broiler Housing: Correlation with Incidence of Health Issues por 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

Materias: “…machine learning…”
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Assessing the biophysical factors affecting irrigation performance in rice cultivation using remote sensing derived information por Sawadogo, A., Dossou-Yovo, Elliott Ronald, Kouadio, L., Zwart, Sander J., Traoré, F., Gundogdu, K. S.

Materias: “…machine learning…”
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Agricultura digital y servicios agroclimáticos: Modernizando los servicios de extensión en el sector arrocero para mejorar la adaptación al clima por Barrios Perez, Camilo

Materias: “…machine learning…”
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Semantic Web and social web heading towards living documents in the life sciences por García Castro, A., Labarga, A, García, Leyla, Giraldo, O, Montana, C, Bateman, JA

Materias: “…learning…”
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Strengthening capacity to achieve Eco-Efficiency through agricultural research for development por Staiger Rivas, Simone, Álvarez, S., Ashby, Jacqueline A., Lundy, Mark M., Muthoni Andriatsitohaina, Rachel, Victoria, P.A., Quiróz, C.A., Sette, Cristina, Rajasekharan, Maya, Russell, N.

Materias: “…learning…”
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Formulate equitable climate-smart agricultural policies por Ampaire, Edidah L., Acosta, Mariola, Mwongera, Caroline, Läderach, Peter R.D., Eitzinger, Anton, Lamanna, Christine, Mwungu, Chris Miyinzi, Shikuku, Kelvin Mashisia, Twyman, Jennifer, Winowiecki, Leigh Ann

Materias: “…learning…”
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A comparison between support vector machine and water Cloud model for estimating crop leaf area index por 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

Materias: “…Machine Learning…”
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Learning networks in innovation systems at sector / regional level in Argentina: Winery and dairy industries por Sanchez, Guillermo, Bisang, Roberto Oscar

Materias: “…Learning…”
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Multi-scale governance and data for sustainable development por Pastor Escuredo, David, Gardeazábal Monsalve, Andrea, Koo, Jawoo, Imai, Asuka, Treleaven, Philip

Materias: “…federated 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... por Ajith, S., Vijayakumar, S., Elakkiya, N.

Materias: “…machine learning…”
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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... por 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

Materias: “…machine learning…”
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