Resultados de búsqueda - "learning"

INFINITy : A fast machine learning-based application for human influenza A and B virus subtyping por Cacciabue, Marco Polo Domingo, Marcone, Débora Natalia

Materias: “…Machine Learning…”
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What can we learn from the ecophysiology of plants inhabiting extreme environments? From ‘sherplants’ to ‘shercrops’ por Flexas, Jaume, Fernie, Alisdair R., Usadel, Björn, Alonso-Forn, David, Ardiles, Victor, Ball, Marilyn C., Ballesteros, Daniel, Bravo, Leon, Brodribb, Tim J., Carriquí, Marc, Ergo, Veronica Vanesa, Gago, Jorge

“…In particular, we propose a pathway for developing ‘shercrops’ learning from ‘sherplants’, debate whether some of the already studied species may have really broken the aforementioned trade-off, and present a number of interesting unforeseen discoveries made when studying plants from extreme climates.…”
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The ALS gene as genetic target in CRISPR/ cas approaches: what have we learned so far? por Darqui, Flavia Soledad, Hopp, Horacio Esteban, Lopez Bilbao, Marisa Gisela

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Visible-NIR reflectance spectroscopy and manifold learning methods applied to the detection of fungal infections on citrus fruit por Lorente, Delia, Escandell-Montero, P., Cubero, Sergio, Gómez-Sanchís, Juan, Blasco, José

“…Three different manifold learning methods (principal component analysis, factor analysis and Sammon mapping) were investigated to transform the high-dimensional spectral data into meaningful representations of reduced dimensionality containing the essential information. …”
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Discrimination of common defects in loquat fruit cv. ‘Algerie’ using hyperspectral imaging and machine learning techniques por Munera, Sandra, Gómez-Sanchís, Juan, Aleixos, Nuria, Vila-Francés, Joan, Colelli, Giancarlo, Cubero, Sergio, Soler, Esteban, Blasco, José

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Coffee growers make improved pest management decisions through group learning and experimentation by crop stage por Guharay, F, Jimenez, C, Aguilar, A, Mendoza, R, Monterrey, J, Monterroso, D, Staver, C, Calderon, M

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Are we learning? Strengthening local people's capacities to facilitate the recuperation of degraded pasture lands in Central America por Bautista Solís, Pável

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Dilemmas and learning accounts around the Traveston Dam proposal on the Mary River (South East Queensland of Australia) por Argyroudi, Anna

“…The clearly expressed dilemmas, visions and actions of the people in the Valley have emerged as the result of a learning process throughout the years-that is a learning of what to do in order to co-exist with the Mary River and why is this meaningful to the community. …”
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“Taking technology to scale”: Learning from the Stress Tolerant Rice for Africa and South Asia (STRASA) project por Bergvinson, David

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Monitoreo y gestión inteligente de cultivos : alertas preventivas y sistema de iluminación suplementario

Materias: “…MACHINE LEARNING…”
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Monitoring spatial-temporal variations of surface areas of small reservoirs in Ghana’s Upper East Region using Sentinel-2 satellite imagery and machine learning por Ghansah, B., Foster, T., Higginbottom, T. P., Adhikari, R., Zwart, Sander J.

Materias: “…machine learning…”
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Toolkit Smart-Valleys por CGIAR Research Program on Rice

Materias: “…learning…”
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Roving Workshop Approach to CSA & CSV Scaling por CGIAR Research Program on Climate Change, Agriculture and Food Security

Materias: “…learning…”
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International Wheat Yield Partnership (IWYP) Hub at CIMMYT under WHEAT FP2: A good example of CGIAR/non-CGIAR cross-project learning and translational research por CGIAR Research Program on Wheat

Materias: “…learning…”
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Satellite-based tracking of agricultural adaptation progress por Reymondin, Louis, Golden, Aaron, Spillane, Charles

Materias: “…machine learning…”
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Playing games to strengthen groundwater governance in rural India por Meinzen-Dick, Ruth S., Bruns, Bryan Randolph, Sanil, Richu

Materias: “…learning…”
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Methylation in the CHH context allows to predict recombination in rice por Peñuela, Mauricio, Gallo-Franco, Jenny Johana, Finke, Jorge, Rocha, Camilo, Gkanogiannis, Anestis, Ghneim-Herrera, Thaura, Lorieux, Mathias

Materias: “…machine learning…”
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CGIAR Initiative on AgriLAC Resiliente: Annual Technical Report 2022 por CGIAR Initiative on AgriLAC Resiliente

Materias: “…learning…”
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Machine-supported decision-making to improve agricultural training participation and gender inclusivity por Reeves, Norman Peter, Ramadan, Ahmed, Sal y Rosas Celi, Victor Giancarlo, Medendorp, John William, Harun-Ar-Rashid, Krupnik, Timothy J., Lutomia, Anne Namatsi, Bello-Bravo, Julia, Pittendrigh, Barry Robert

Materias: “…machine learning…”
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Toward sustainable land use planning: Land use mapping for Nandi County, Kenya por Hettiarachchi, Upeksha, Zhang, Wei, Zhe, Guo, Kibet, Walter

Materias: “…machine learning…”
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