Search Results - "Learning"

Transforming soil quality index predictions in the Nile River Basin using hybrid stacking machine learning techniques by Singha, Chiranjit, Sahoo, Satiprasad, Govind, Ajit

Subjects: “…machine learning…”
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From theory to practice: lessons from transformative learning through a net-zero design competition by Mehmood, A., Cheema, Abdur Rehman, Salam, M., Ahmed, S. U. D., Moghayedi, A., Vassilev, V., Aburamadan, R.

Subjects: “…experiential learning…”
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Global insights into nitrogen losses and efficiency in rice, wheat, and maize cultivation by Chakraborty, Debashis, Ladha, Jagdish Kumar, Das, Bappa, Dharamvir Singh Rana, Gathala, Mahesh Kumar, Jat, Mangi Lal, Krupnik, Timothy J.

Subjects: “…machine learning…”
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Advancing Soil Moisture Prediction Using Satellite and UAV-based Imagery with Machine Learning Models by Hussain, S., Arshad, M., Cheema, Muhammad Jehanzeb Masud, Qamar, M. U., Wajid, S. A., Daccache, A.

Subjects: “…machine learning…”
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Tracking Rangeland Degradation from Prosopis Invasion in Kenyan Rangeland: A Multi-Source Approach Combining Remote Sensing, Machine Learning and Citizen Science by Cherotich, Fredah, Galgallo, Diba, Dhulipala, Ram, Whitbread, Anthony M, Paliwal, Ambica

Subjects: “…machine learning…”
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Insecticide use, farmers’ self-reported health status, and genetically modified cowpea in Nigeria: Findings from a clustered randomized controlled trial with causal by Amare, Mulubrhan, Andam, Kwaw S., Spielman, David J., Bamiwuye, Temilolu, Nwagboso, Chibuzo, Zambrano, Patricia, Chambers, Judith A.

Subjects: “…machine learning…”
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Simple rules for catalyzing collective action in natural resource management contexts by Colfer, C.J.P.

Subjects: “…learning…”
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Aturan-aturan sederhana katalisasi aksi kolektif dalam pengelolaan sumberdaya alam by Colfer, C.J.P.

Subjects: “…learning…”
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Adaptive collaborative management: a conceptual model by Prabhu, Ravi, McDougall, C., Fisher, R.

Subjects: “…social learning…”
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Conclusiones: gestionar el aprender sobre el hacer, un propósito que debe hacerse explícito by Ferreira, SM, Staiger Rivas, Simone, Villa, C.

Subjects: “…learning…”
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Closing the Relevance Gap: Lessons in Co-Developing Gender Transformative Research Approaches with Development Partners and Communities by Ferdous, N., Jost, Christine, Kristjanson, Patricia M.

Subjects: “…learning capacity…”
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Engendered orange-fleshed sweetpotato project planning, implementation, monitoring and evaluation: A learning kit. 3: Writing full proposals by Mbabu, A.N., Franca, Z.P., Mulongo, G., Munyua, H.M., Ojwang, F., Low, Jan W.

Subjects: “…learning…”
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Knowledge-based planning for innovation systems and agricultural research for development: the case of SABRN by Muthoni Andriatsitohaina, Rachel, Beelen, Koen, Staiger Rivas, Simone, Chirwa, Rowland, Bheenick, Krishan

Subjects: “…learning…”
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Estudios sobre el comportamiento de aprendizaje de la abeja revelan su capacidad para discriminar tipos de polen by Pietrantuono, Ana Laura, Requier, Fabrice, Fernandez Arhex, Valeria Cristina, Winter, Josefina, Huerta, Guillermo Jose, Guerrieri, Fernando

Subjects: “…Animal Learning…”
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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

Subjects: “…Deep Learning…”
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Global habitat suitability of Spodoptera frugiperda (JE Smith) (Lepidoptera, Noctuidae): key parasitoids considered for its biological control by Tepa-Yotto, Ghislain T., Tonnang, Henri E.Z., Goergen, Georg E., Subramanian, S., Kimathi, E.K., Abdel-Rahman, E.M., Flo, D., Thunes, K.H., Fiaboe, K., Niassy, S., Bruce, A., Mohamed, S.A., Tamo, Manuele, Ekesi, S., Saethre, M.G.

Subjects: “…machine learning…”
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Reference soil groups map of Ethiopia based on legacy data and machine learning technique: EthioSoilGrids 1.0 by Ali, Ashenafi, Erkossa, Teklu, Gudeta, Kiflu, Abera, Wuletawu, Mesfin, Ephrem, Mekete, Terefe, Haile, Mitiku, Haile, Wondwosen, Abegaz, Assefa, Tafesse, Demeke, Belay, Gebeyhu, Getahun, Mekonen, Beyene, Sheleme, Assen, Mohamed, Regassa, Alemayehu, Selassie, Yihenew G., Tadesse, Solomon, Abebe, Dawit, Walde, Yitbarek, Hussien, Nesru, Yirdaw, Abebe, Mera, Addisu, Admas, Tesema, Wakoya, Feyera, Legesse, Awgachew, Tessema, Nigat, Abebe, Ayele, Gebremariam, Simret, Aregaw, Yismaw, Abebaw, Bizuayehu, Bekele, Damtew, Zewdie, Eylachew, Schulz, Steffen, Tamene, Lulseged D., Elias, Eyasu

Subjects: “…machine learning…”
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Guinayangan CSV experience guided design of IDRC-supported project in Myanmar to establish CSVs in 4 distinct agro-ecosystems by CGIAR Research Program on Climate Change, Agriculture and Food Security

Subjects: “…learning…”
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Guinayangan CSV experience guides Philippine DA's development of AMIA villages, the Philippine adaptation of CSV approach by CGIAR Research Program on Climate Change, Agriculture and Food Security

Subjects: “…learning…”
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Catalyzing and learning from private sector engagement: monitoring to generate evidence and learning by Caldas de Oliveira, Bernardo, Francesconi, Wendy, Rodríguez Sánchez, Beatriz, Deboni, Fabio

Subjects: “…learning…”
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