Resultados de búsqueda - "Learning"

Changed behavior in the house cricket Acheta domesticus : predetermined or an effect of learning? por Olofsson, Caroliné

Materias: “…learning…”

Predicting yields using biophysical crop simulations, machine learning and remote sensing in India por CGIAR Platform for Big Data in Agriculture

Materias: “…learning…”
Enlace del recurso

Ultra-processed food consumption is associated with variations in daily routines in elementary schoolchildren during the COVID-19 pandemic in Chile por Fretes, Gabriela, Corvalán, Camila, Economos, Christina D., Wilson, Norbert L.W., Cash, Sean B.

Materias: “…learning…”
Enlace del recurso

Mutual learning and partnership among developing countries in Asia can help address alarming food safety issues por Chi Nguyen

Materias: “…learning…”
Enlace del recurso

The Gender Equality in Research Scale: A tool for monitoring and encouraging progress on gender integration in research for and in development por Paez Valencia, Ana Maria, Ihalainen, Markus, Elias, Marlène, Sijapati Basnett, Bimbika

Materias: “…learning…”
Enlace del recurso

Terra-i+ Using machine learning to manage impacts of coffee production in Ocotepeque, Honduras por Alliance of Bioversity International and CIAT

Materias: “…machine learning…”
Enlace del recurso

Terra-i + Using machine learning to manage impacts of coffee production in Ocotepeque por Alliance of Bioversity International and CIAT

Materias: “…machine learning…”
Enlace del recurso

Business model testing and advisory with Root Capital and Sustainable Food Lab por Root Capital

Materias: “…machine learning…”
Enlace del recurso

Understanding users formal meetings por Alliance of Bioversity International and CIAT

Materias: “…machine learning…”
Enlace del recurso

Mining the gaps:using machine learning to map a million data points from agricultural research from the global south por Porciello, J., Lipper, L., Bourne, T., Ivanina, M., Lin, S., Langleben, S.

Materias: “…machine learning…”
Enlace del recurso

Gender dimensions in the complexity of managing forest resource: learning from Berau District, Indonesia por Sakuntaladewi, Niken

Materias: “…learning…”
Enlace del recurso

Customized New Extensionist Learning Kit for Rwanda por CGIAR Research Program on Policies, Institutions, and Markets

Materias: “…learning…”
Enlace del recurso

Desarrollo e implementación de un sistema de apoyo para laboratorios con dispositivos móviles - pockets en el Centro Internacional de la Papa por Verano, P.E.

Materias: “…e-learning…”
Enlace del recurso

Time to scale is now-now: CGIAR-GIZ scaling networking and learning event por Schut, Marc, Pircher, Thomas

Materias: “…learning…”
Enlace del recurso

Interpretable machine learning methods to explain on-farm yield variability of high productivity wheat in Northwest India por Nayak, Harisankar, Silva, ‪João Vasco, Parihar, Chiter Mal, Krupnik, Timothy J., Sena, Dipaka Ranjan, Kakraliya, S., Jat, Hanuman Sahay, Sidhu, Harminder Singh, Sharma, Parbodh Chander, Jat, Mangi Lal, Sapkota, Tek Bahadur

Materias: “…machine learning…”
Enlace del recurso

Developing timely and actionable drought forecasts for the Limpopo River Basin por Montes, Carlo

Materias: “…machine learning…”
Enlace del recurso

Agriculture, Food and Nutrition Security: Concept, Datasets and Opportunities for Computational Social Science Applications por Amjath-Babu, T.S., López Ridaura, Santiago, Krupnik, Timothy J.

Materias: “…machine learning…”
Enlace del recurso

Untangling the effect of soil quality on rice productivity under a 16-years long-term fertilizer experiment using conditional random forest por Garnaik, Saheed, Samant, Prasanna Kumar, Mandal, Mitali, Mohanty, Tushar Ranjan, Dwibedi, Sanat Kumar, Patra, Ranjan Kumar, Mohapatra, Kiran Kumar, Wanjari, Ravi H., Sethi, Debadatta, Sena, Dipaka Ranjan, Sapkota, Tek Bahadur, Nayak, Jagmohan, Patra, Sridhar, Parihar, Chiter Mal, Nayak, Harisankar

Materias: “…machine learning…”
Enlace del recurso

Optimal sample size and composition for crop classification with Sen2-Agri’s random forest classifier por Schulthess, Urs, Rodrigues, Francelino, Taymans, Matthieu, Bellemans, Nicolas, Bontemps, Sophie, Ortíz Monasterio, Jose Iván, Gerard, Bruno G., Defourny, Pierre

Materias: “…machine learning…”
Enlace del recurso

Report on Innovation Packages and Scaling Readiness (IPSR) and Reflect: Focus Group Discussion part of the 2022 Technical Report Learning and Optimization process por CGIAR System Management Office

Materias: “…learning…”
Enlace del recurso