Search Results - "artificial intelligence"

Use of Artificial Intelligence for Rice Crop Manager backend datasets in Odisha by Gakhar, Shalini, Jardinero, Benedict, Bharti, Preeti, Castillo, Rowena, Vila, Jerome, Sharma, Sheetal

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Human centered design and artificial intelligence. Working group on HCD and AI. by Ortiz-Crespo, Berta

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Responsible Use of Artificial Intelligence in Research (and where to stick to human intelligence) by Domelevo Entfellner, Jean-Baka

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Real-time artificial intelligence driven diagnostic that can be used to assess diets by CGIAR Research Program on Agriculture for Nutrition and Health

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Can artificial intelligence and space technology transform livestock insurance and rangeland management? by Onyango, Polycarp Otieno, Paliwal, Ambica

“…A new study shows that artificial intelligence (AI) could improve the accuracy of index-based livestock insurance (IBLI) satellite assessments in regions affected by invasive plant species. …”
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Artificial Neural Networks in Agriculture, the core of artificial intelligence: What, When, and Why by Castillo-Gironés, Salvador, Munera, Sandra, Martinez-Sober, Marcelino, Blasco, José, Cubero, Sergio, Gómez-Sanchis, Juan

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Predicting rice phenotypes with meta and multi-target learning by Orhobor, Oghenejokpeme I., Alexandrov, Nickolai N., King, Ross D.

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Climate change effects on pathogen emergence: Artificial intelligence to translate big data for mitigation by Garrett, K.A., Bebber, D.P., Etherton, B.A., Gold, K.M., Plex Sulá, A.I., Selvaraj, Michael G.

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Smart breeding driven by big data, artificial intelligence, and integrated genomic-enviromic prediction by Yunbi Xu, Zhang Xingping, Huihui Li, Hongjian Zheng, Jianan Zhang, Olsen, Michael, Varshney, Rajeev K., Boddupalli, P.M., Qian Qian

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How can artificial intelligence-powered chatbots help policymakers? A roadmap for Kenya by Akuku, Boniface, Breisinger, Clemens, Karugia, Joseph, Koo, Jawoo, Keenan, Michael, Ndegwa, Richard

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Artificial Intelligence in Genebanks: Seed Multispectral Analysis for Germplasm Integrity and Targeted Breeding Traits by Zaher, Oumaima, Choukri, Hasnae, Moulakat, Adil, Tsivelikas, Athanasios, Kehel, Zakaria

“…Artificial Intelligence in Genebanks: Seed Multispectral Analysis for Germplasm Integrity and Targeted Breeding Traits.…”
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RGB Image Dataset of Urochloa Hybrids for High-Throughput Phenotyping and Artificial Intelligence Applications by Arrechea-Castillo, Darwin Alexis, Espitia Buitrago, Paula Andrea, Florian Vargas, David Alberto, Estupinan Arboleda, Ronald David, Velazquez Hernandez, Riquelmer, Camelo Munevar, Rodrigo Andres, Cardoso Arango, Juan Andres

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Integration of Artificial Intelligence in Seasonal to Sub‑Seasonal Forecasting Systems in West Africa and the Sahel by Houngnibo, Mandela C., Ali, Abdou, Assoumana, Boubacar Toukal, Minoungou, Bernard, Segnon, Alcade Christel, Zougmore, Robert Bellarmin

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Breeding 5.0: Artificial intelligence (AI)-decoded germplasm for accelerated crop innovation by Fu, Jiayi, Zheng, Shouzhi, Fan, Longjiang, Zheng, Xiaoming, Qian, Qian

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Collaborative Solutions: Leveraging Artificial Intelligence for Resilient Agriculture, Energy, and Risk Systems in Africa by African Climate Policy Centre, Accelerating Impacts of CGIAR Climate Research for Africa, United Nations Office for Disaster Risk Reduction

“…This mandated session was centered on the use of Artificial Intelligence (AI), Earth Observation (EO), and material innovation to enhance climate resilience in Africa. …”
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Implementing artificial intelligence to measure meat quality parameters in local market traceability processes by Alvarez García, Wuesley Yusmein, Mendoza, Laura, Muñoz Vílchez, Yudith Yohany, Casanova Núñez Melgar, David, Quilcate Pairazaman, Carlos

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AI for Sustainable Rice: How Artificial Intelligence Could Lower Barriers to Access Carbon Finance by Mantle Labs

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Artificial intelligence research: A review on dominant themes, methods, frameworks and future research directions by Ofosu-ampong, Kingsley

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

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

“…To untangle this complexity, this research combined concepts of classic gravity model with machine learning techniques, relying on Explainable Artificial Intelligence techniques (xAI) to enhance the transparency of the predictive models. …”
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