Search Results - Intelligence levels.

Hybrid object detection and generative ai framework for automated river gauge plate reading and discharge estimation by Kayathri, Vigneswaran, Retief, Hugo, Clifford-Holmes, J., Garcia Andarcia, Mariangel, Tennakoon, Hansaka

Subjects: “…artificial intelligence…”
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Artificial intelligence in plant breeding by Farooq, Muhammad Amjad, Shang Gao, Hassan, Muhammad Adeel, Zhangping Huang, Awais Rasheed, Hearne, Sarah, Prasanna, Boddupalli M., Xinhai Li, Huihui Li

“…Harnessing cutting-edge technologies to enhance crop productivity is a pivotal goal in modern plant breeding. Artificial intelligence (AI) is renowned for its prowess in big data analysis and pattern recognition, and is revolutionizing numerous scientific domains including plant breeding. …”
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Gender differences in perception of artificial intelligence-based tools by Ofosu-ampong, Kingsley

“…Participation of girls in Science, Technology, Engineering, and Mathematics (STEM) subjects at the higher education (HE) level continues to lag behind that of boys and consequently may affect artificial intelligence proliferation in Ghana. …”
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Global Market Intelligence Platform Annual Report 2025 by Paguirigan, Neale, Lenaerts, Bert, Bayot, Ruvicyn, Demont, Matty, Ynion, Jhoanne, Badayos, Gerdino, De Leon, Dehner

“…Recent improvements have strengthened the features and functionality of GloMIP and its portals, delivering better performance, user experience, and improved modelling of projected benefits indicators for Nutrition and Poverty at national and market segment levels. MI and GloMIP hosts a wide array of market intelligence products, such as briefs, posts, podcasts, while strengthening B4T communications and supporting the launch of the first B4T newsletter. …”
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SukhaRakshak AI - anticipatory drought intelligence for India by Amarnath, Giriraj, Kapoor, Sanya, Bhatpuria, Dhyey, Padhee, Suman Kumar, Rao, K. V., Sudhishri, S., Sikka, Alok

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Protocol for evidence synthesis of market intelligence: Application to rice in the global South by Custodio, Marie Claire, De Steur, Hans, Demont, Matty

“…Demand-oriented crop breeding relies on market intelligence to support market segmentation, target product profile (TPP) design, alignment of breeding pipelines, and prioritization and allocation of investments. …”
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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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Artificial intelligence research: A review on dominant themes, methods, frameworks and future research directions by Ofosu-ampong, Kingsley

“…This article presents an analysis of artificial intelligence (AI) in information systems and innovation-related journals to determine the current issues and stock of knowledge in AI literature, research methodology, frameworks, level of analysis and conceptual approaches to identify research gaps for future investigations. …”
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Foodgravity: understand food flows using classic gravity model and explainable artificial intelligence techniques by Dusabe, B.

“…The study recommends the integration of market level flow data, the scope and temporal expansion for a more granular analysis.…”
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Foodgravity: understand food flows using classic gravity model and explainable artificial intelligence techniques by Dusabe, B.

“…The study recommends the integration of market level flow data, the scope and temporal expansion for a more granular analysis.…”
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Quantifying the health impact of crop breeding: Revisiting the Disability-Adjusted Life Years Approach by Lenaerts, Bert

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Integrating earth observation, artificial intelligence, and Crop modelling for maize yield estimation in smallholder farming systems in Kenya by Owuor, C.A.

“…Calibration and validation will be conducted using field-level yield data from diverse agroecological zones in Kenya to ensure robustness and transferability of the results. …”
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Integrating climate intelligence into digital agroadvisory systems: A scalable multi model framework for AgWise Engine by Tibebe, Degefie, Seid, Jemal, Abera, Wuletawu, Saito, Kazuki, Mkuhlani, Siyabusa, Leroux, Louise, Mabilangan, Abigail, Ghosh, Aniruddha, Kihara, Job

“…The strategic goal for the AgWise1 Climate Intelligence (CI) integration is to engineer a fundamental paradigm shift: climate predictions must evolve from passive informational products into active decision-input variables that directly parameterize and modulate underlying agronomic optimization algorithms. …”
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Integration of Artificial Intelligence (AI) to generate personalized weather and crop advisories: A case study of Meghdoot app in India by Singh, Kanika, Dhulipala, Ram, Billu, Naveen, Chawala, Kapil, Vishnoi, Lata

“…To address this issue, the report delves into the impact of Meghdoot, a mobile application designed in India to provide tailored crop management recommendations alongside district-level meteorological data. To further improve the provisioning of crop management advisories, Artificial Intelligence (AI) techniques were used in a pilot project as an alternative to the existing labor-intensive manual process. …”
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Classifying the risk of forest loss in the Peruvian amazon rainforest: An alternative approach for sustainable forest management using artificial intelligence by Goycochea Casas, Gianmarco, Baselly Villanueva, Juan Rodrigo, Coimbra Limeira, Mathaus Messias, Eleto Torres, Carlos Moreira Miquelino, Garcia Leite, Hélio

“…Understanding changes in forest cover and assessing the level of risk is a permanent concern for numerous scientists and forest authorities. …”
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Enhancing market segmentation with GloMIP's Impact Opportunities Portal by Lenaerts, Bert, Paguirigan, Neale Marvin, Demont, Matty

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AI Monitoring Approach to Fill National Food Loss and Waste Data Gaps by Guo, X., Axmann, H.B., Soethoudt, J.M., Kok, M.G.

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Ground reference dataset for crop type mapping and monitoring in four districts of Rwanda by Kenduiywo, Benson Kipkemboi, Wahome, Anastasia Mumbi, Sande, Stephen Ngondi, Chemutt, Joseph Kipkoech

“…The questionnaires were designed to capture both geospatial and contextual farm-level information relevant to crop mapping and classification. …”
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AI-assisted dietary assessment and personalized “nudges” in urban Ghana: Preparing for scale-up by Gelli, Aulo, Folson, Gloria, Nwabuikwu, Odiche, Bannerman, Boateng, Ador, Gabriel, Atadze, Vicentia, Asante, Millicent, McCloskey, Peter, Nguyen, Phuong Hong, Hughes, David

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The state of the field for research on agrifood systems by Porciello, Jaron, Skidan, Volha, Ambikapathi, Ramya, Boonabaana, Brenda, Guerra, Jill, Lidder, Preetmoninder, Piñeiro, Valeria, Phillips, Lauren, Savilaakso, Sini, Schuster, Monica, Sheikh, Hafsa, Tufan, Hale, Witkowski, Kelly

“…‘The State of the Field for Research on Agrifood Systems’ uses artificial intelligence (AI) to analyse global research distribution from the past 13 years. …”
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