Search Results - "machine learning"

Big data analysis to understanding online songbird trade in Indonesia: What are the most traded species? by Center for International Forestry Research

Subjects: “…machine learning…”
Get full text

Assessing the performance of the NextGen agroadvisory on wheat yields in Ethiopia by Liben, Feyera, Abera, Wuletawu, Ebrahim, Mohammed, Mesfin, Tewodros, Tesfu, Daniel, Gashaw, Getachew, Bekele, Hawinet, Tilaye, Asmalu, Erkossa, Teklu, Ayele, Kebede, Adimassu, Zenebe, Tamene, Lulseged D.

Subjects: “…machine learning…”
Get full text

Machine learning- based gridded soil mapping for Kapiti research station and wildlife conservancy, Kenya by Paliwal, Ambica, Cherotich, Fredah, Leitner, Sonja, Pearce, F., Rufino, M., Quinton, J., Dhulipala, Ram, Salavati, M., Gluecks, Ilona V., Whitbread, Anthony M.

Subjects: “…machine learning…”
Get full text

Discriminating Robusta coffee (Coffea canephora) cropping systems using leaf-level hyperspectral data by Kebede, G., Mudereri, B.T., Abdel-Rahman, E.M., Mutanga, O., Landmann, T., Odindi, J., Motisi, N., Pinard, F., Tonnang, H.E.Z.

Subjects: “…machine learning…”
Get full text

Detecting cumulative effects of inputs within the flexible production function framework through LASSO shrinkage estimation: Implications for potassium fertilizer use in India by Takeshima, Hiroyuki, Kishore, Avinash

Subjects: “…machine learning…”
Get full text

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

Subjects: “…machine learning…”
Get full text

Demand intelligence: an extended descriptor report for sub-indicators by Sartas, M., Konlambigue, M.

Subjects: “…machine learning…”
Get full text

Redes neuronales para la identificación de enfermedades en el cultivo de tomate (Solanum lycopersicum L.) en Honduras by Erazo V., Jorge D., Uema H., Ken S.

Subjects: “…Machine Learning…”
Get full text

Integrating satellite and climate data to predict wheat yield in Australia using machine learning approaches by Cai, Y., Guan, K., Lobell, D. B., Potgieter, A.B., Wang, S., You, Liangzhi

Subjects: “…machine learning…”
Get full text

Machine learning innovations to improve maize nutrient management recommendations in the eastern IndoGangetic Plains by CGIAR Research Program on Maize

Subjects: “…machine learning…”
Get full text

Categorizing the songbird market through big data and machine learning in the context of Indonesia’s online market by Okarda, B., Muchlish, U., Kusumadewi, S.D., Purnomo, H.

“…The authors found that the machine learning models produced a high level of accuracy in distinguishing relevant ads and identified the songbirds’ taxa. …”
Get full text

Early detection of plant virus infection using multispectral imaging and spatial-spectral machine learning by Peng, Y., Dallas, M.M., Ascencio‑Ibanez, J.T., Hoyer, J.S., Legg, James P., Hanley-Bowdoin, L., Grieve, B., Yin, H.

Subjects: “…machine learning…”
Get full text

Machine learning technique unraveled subspecies-specific ionomic variation with the preferential mineral enrichment in rice by Tiozon, Rhowell N., Buenafe, Reuben James, Jain, Vinay, Sen, Partha, Molina, Lilia R., Anacleto, Roslen, Sreenivasulu, Nese

Subjects: “…machine learning…”
Get full text

Using explainable machine learning techniques to unpack farm-level management x climate interactions by Ramírez Villegas, Julián Armando, Jaimes, Diana, Gonzalez Rodriguez, Carlos Eduardo, Llanos, Lizeth, Jimenez, Daniel, Gardeazabal, Andrea, Estrada, Oscar, Nuñez, Daniel

Subjects: “…machine learning…”
Get full text

Grow the pie, or have it? Using machine learning to impact heterogeneity in the Ultra-poor graduation model by Chowdhury, Reajul Alam, Ceballos-Sierra, Federico, Sulaiman, Munshi

Subjects: “…machine learning…”
Get full text

Mapping major land use types in Nandi County using remote sensing and machine learning by Guo, Zhe, Walter, Kibet

Subjects: “…machine learning…”
Get full text

Metabolomics and machine learning technique revealed that germination enhances the multi-nutritional properties of pigmented rice by Tiozon, Rhowell N., Jr., Sreenivasulu, Nese, Alseekh, Saleh, Sartagoda, Kristel June D., Usadel, Björn, Fernie, Alisdair R.

Subjects: “…machine learning…”
Get full text

Remote sensing and machine learning for food crop production data in Africa post-COVID-19 by Ly, Racine, Dia, Khadim, Diallo, Mariam A.

Subjects: “…machine learning…”
Get full text

Evaluating the dry matter content of raw yams using hyperspectral imaging spectroscopy and machine learning by Adesokan, M., Otegbayo, B., Alamu, E.O., Olutoyin, M.A., Maziya-Dixon, B.

Subjects: “…machine learning…”
Get full text

Predicting aflatoxin risk in maize using machine learning and satellite data in East and Southern Africa by Gachoki, Stella, Muthoni, Francis, Mahuku, George S., Atehnkeng, J., Tripathi, Leena

Subjects: “…machine learning…”
Get full text