Resultados de búsqueda - "Learning"

Designing STIBs and ToC Frameworks for Learning Labs por Jain, Harsha, Chadha, Deepali, Gartaula, Hom N., Mukhopadhyay, Prama, Goel, Kritika, Dwevedi, Anusha, Shivhare, Richa, Puskur, Ranjitha

Materias: “…learning labs…”
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Mechanisms for increasing the accountability of teachers and schools in rural Pakistan to improve learning outcomes por Asad, Saher, Habib, Masooma, Karachiwalla, Naureen, Kosec, Katrina, Leaver, Clare, ur Rehman, Attique

Materias: “…learning…”
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Reforming educator accountability systems: Evidence from Pakistan por Asad, Saher, Habib, Masooma, Karachiwalla, Naureen, Kosec, Katrina, Leaver, Clare, ur Rehman, Attique

Materias: “…learning…”
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Farmers' co-learning for effective agroforestry and improved animal welfare in Humbo District, Ethiopia por Berhe, Tsega, Gelan, Eyob, Mokria, Mulugeta, Alemayehu, Gezahegn, Doyle, Rebecca

Materias: “…learning capacity…”
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Application of a multi-layer convolutional neural network model to classify major insect pests in stored rice detected by an acoustic device por Balingbing, Carlito B., Kirchner, Sascha, Siebald, Hubertus, Kaufmann, Hans-Hermann, Gummert, Martin, Van Hung, Nguyen, Hensel, Oliver

Materias: “…machine learning…”
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Prediction of spatial heterogeneity in nutrient-limited sub-tropical maize yield: Implications for precision management in the eastern Indo-Gangetic Plains por Ahmed, Zia Uddin, Krupnik, Timothy J., Timsina, Jagadish, Saiful Islam, Hossain, M. Khaled, Alanuzzaman Kurishi, A.S.M., Shah-Al Emran, Harun-Ar-Rashid, McDonald, Andrew, Gathala, Mahesh K.

Materias: “…machine learning…”
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An XGBoost approach to predictive modelling of Rift Valley fever outbreaks in Kenya using climatic factors por Mulwa, D., Kazuzuru, B., Misinzo, G., Bett, Bernard K.

Materias: “…machine learning…”
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Color and Grey-Level Co-Occurrence Matrix Analysis for Predicting Sensory and Biochemical Traits in Sweet Potato and Potato por Nantongo, J.S., Serunkuma, E., Burgos, G., Nakitto, M., Kitalikyawe, J., Mendes, T., Davrieux, F., Ssali, R.T.

Materias: “…machine learning…”
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High-resolution crop-type mapping in northern Ghana por Alabi, T., Muthoni, F., Uponi, J., Alabi, W., Oluwaleye, J.

Materias: “…machine learning…”
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Soybean rust early warning system in East and Southern Africa por Gachoki, S., Muthoni, F., Mureithi, H., Tripathi, L.

Materias: “…machine learning…”
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Mapping aflatoxin risk using machine learning and remote sensing in East and Southern Africa por Gachoki, S., Muthoni, F., Mahuku, G., Atehnkeng, J., Njeru, N., Kamau, J., Tripathi, L.

Materias: “…machine learning…”
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EasyIDP: A python package for intermediate data processing in UAV-based plant phenotyping por Wang, Haozhou, Duan, Yulin, Shi, Yun, Kato, Yoichiro, Ninomiya, Seishi, Guo, Wei

Materias: “…machine learning…”
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Machine Learning Approach for Prediction of Area Under Cultivation and Production for Vegetatively Propagated Crops por Ahishakiye, E., Ogero, K., Namada, S., Rajendran, S.

Materias: “…machine learning…”
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Mature products & assets: AGROTUTOR por Excellence in Agronomy

Materias: “…machine learning…”
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Ukama Ustawi’s Learning Alliance: scoping study - final report por Kumwenda, H., Kakuwa, B., Odeke, M., Podisi, B., Nohayi, Ngowenani

Materias: “…learning…”
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Dataset: Forage grasses in crop fields from ultra-high spatial resolution UAV-based imagery por Cardoso Arango, Juan Andres, Jauregui, Rosa Noemi, Camelo-Munevar, Rodrigo Andres, Ruiz-Hurtado, Andres Felipe, Arrechea-Castillo, Darwin Alexis

Materias: “…machine learning…”
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Fine-tuned AI for tracking policy demands and studies por Yego, Francis, Song, Chun, Laporte, Marie-Angelique

Materias: “…machine learning…”
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Which machine learning algorithm is best suited for estimating reference evapotranspiration in humid subtropical climate? por Deb, P., Kumar, V., Urfels, A., Lautze, Jonathan F., Kamboj, B. R., Sharma, J. R., Yadav, S.

Materias: “…machine learning…”
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Machine learning approach to predicting Rift Valley fever disease outbreaks in Kenya por Mulwa, D., Kazuzuru, B., Misinzo, G., Bett, Bernard K.

Materias: “…machine learning…”
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Farmers agronomic management responses to extreme drought and rice yields in Bihar, India por Mkondiwa, Maxwell, Kishore, Avinash, Veettil, Prakashan Chellattan, Sherpa, Sonam, Saxena, Satyam, Pinjarla, Bhavani, Urfels, Anton, Poonia, Shishpal, Ajay, Anurag, Craufurd, Peter, Malik, Ram K., McDonald, Andrew J.

Materias: “…machine learning…”
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