Search Results - "Learning"

Early detection of infection by Penicillium digitatum in oranges using hyperspectral imaging and machine learning by Castillo-Gironés, Salvador, Gómez-Sanchis, Juan, López-Chulia, Marina, Guirao, Alberto, Palou, Lluís, Souza, Ricardo-Lima-de, Blasco, José

Subjects: “…machine learning…”
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Convolutional neural networks to assess bergamot essential oil content in the field from smartphone images by Anello, Matteo, Mateo, Fernando, Bernardi, Bruno, Giuffrè, Angelo Maria, Blasco, José, Gómez-Sanchis, Juan

Subjects: “…Deep learning…”
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Identity frames in knowledge co-creation : facilitators for sustainability transformations by Nyström, Maria

Subjects: “…learning…”

Development of web-based Small-Scale Irrigation Management Information System (SSIMIS) to facilitate data collection, storage, management, and analysis by CGIAR Research Program on Climate Change, Agriculture and Food Security

Subjects: “…learning…”
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Implementing cloud computing for the digital mapping of agricultural soil properties from high resolution UAV multispectral imagery by Pizarro Carcausto, Samuel Edwin, Pricope, Narcisa G., Figueroa Venegas, Deyanira Antonella, Carbajal Llosa, Carlos Miguel, Quispe Huincho, Miriam Rocío, Vera Vilchez, Jesús Emilio, Alejandro Méndez, Lidiana Rene, Achallma Mendoza, Lino, González Tovar, Izamar Estrella, Salazar Coronel, Wilian, Loayza, Hildo, Cruz Luis, Juancarlos Alejandro, Arbizu Berrocal, Carlos Irvin

Subjects: “…Machine learning…”
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Predicting the chlorophyll content of maize over phenotyping as a proxy for crop health in smallholder farming systems by Brewer, K., Clulow, A.D., Sibanda, M., Gokool, S., Naiken, V., Mabhaudhi, Tafadzwanashe

Subjects: “…machine learning…”
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JAL SUTRA: a mobile application to support facilitation of learning games on water management in India by CGIAR Research Program on Policies, Institutions, and Markets

Subjects: “…learning…”
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"How are we doing?", a tool for participatory monitoring and adaptive learning in multi-stakeholder fora by CGIAR Research Program on Policies, Institutions, and Markets

Subjects: “…learning…”
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Inspire Challenge Award: Seeing is believing – Using smartphone camera data by CGIAR Platform for Big Data in Agriculture

Subjects: “…learning…”
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Manual of Operations for the Schools-on-the-Air on Smart Rice Agriculture in the Philippines by CGIAR Research Program on Climate Change, Agriculture and Food Security

Subjects: “…learning…”
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"How are we doing?", a tool for participatory monitoring and adaptive learning in multi-stakeholder fora by CGIAR Research Program on Forests, Trees and Agroforestry

Subjects: “…learning…”
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Project-level Women's Empowerment in Agriculture Index (pro-WEAI) Foundations Module, a distance learning course developed by A4NH gender researchers by CGIAR Research Program on Agriculture for Nutrition and Health

Subjects: “…learning…”
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Getting ahead of the game: Experiential learning for groundwater governance in Ethiopia by ElDidi, Hagar, Zhang, Wei, Gelaw, Fekadu, Petris, Caterina de, Blackmore, Ivy, Teka, Natnael, Yimam, Seid, Mekonnen, Dawit Kelemework, Ringler, Claudia, Meinzen-Dick, Ruth S.

Subjects: “…experiential learning…”
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Climate variability and extremes impact on seasonal occurrence patterns of malaria cases in Senegal [Abstract only] by Jampani, Mahesh, Panjwani, Shweta, Ghosh, Surajit, Sambou, Mame Henriette Astou, Amarnath, Giriraj

Subjects: “…machine learning…”
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Decision-making in a changing climate: From analysis to guided adaptation action in cocoa, coffee and tea farming systems. by Schmidt, Paul, Kumari, Resham, Garcia, Rochelle, Juhrbrandt, Jana, Atienza, Lauro, Peñaflor, Zsarla, Bunn, Christian

Subjects: “…learning capacity…”
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Direct and spillover effects of agricultural advisory services: Evidence from the farm science centre in Uttar Pradesh, India by Varshney, Deepak, Joshi, Pramod Kumar, Dubey, Shantanu Kumar

Subjects: “…learning…”
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IFPRI Forum: Healthy agriculture for healthy people by International Food Policy Research Institute

Subjects: “…learning…”
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Using an indicator framework to assess organizational change in CGIAR breeding programs resulting from Accelerated Breeding 2022–2024 interventions by Quinn, Michael, De Col, Valentina, Coaldrake, Peter, Hearne, Sarah, Mbanjo, Gaby, Biswanath, Das, Ferguson, Morag E., Gemenet, Dorcus, Jacob, Neena, Bänziger, Marianne

Subjects: “…learning…”
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PROGRESS REPORT: Developing Data‑Driven Agronomic Recommendations for Site‑Specific Nutrient Management on Rice in Cambodia by Mabilangan, Abigail, Mkuhlani, Siyabusa, Saito, Kazuki

Subjects: “…machine learning…”
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A robust model based on root morphological and anatomical features to distinguish high and low methane emission rice varieties through machine learning approaches by Roy, Ripon Kumar, Hosseiniyan Khatibi, Seyed Mahdi, Kim, Sung-Ryul, Trijatmiko, Kurniawan Rudi, Diaz, Maria Genaleen Q., Ocampo, Eureka Teresa M., Hernandez, Jose E., Pirmoradi, Saeed, Henry, Amelia, Kohli, Ajay

Subjects: “…machine learning…”
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