Search Results - "machine learning"

Addressing salinity intrusion in the polders of coastal Bangladesh: predictive machine-learning modeling for strategic sluice gate operations by Behera, Abhijit, Sena, Dipaka Ranjan, Hasib, Md. R., Matheswaran, Karthikeyan, Jampani, Mahesh, Mizan, Syed Adil, Islam, Md. J., Alam, R., Mondal, M. K., Sikka, Alok

Subjects: “…machine learning…”
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Advancing food security: rice yield estimation framework using time-series satellite data & machine learning by Tiwari, Varun, Thorp, Kelly, Tulbure, Mirela G., Gray, Joshua, Kamruzzaman, Mohammad, Krupnik, Timothy J., Sankarasubramanian, A., Ardon, Marcelo

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Change point-driven interrupted time series and machine learning models for forecasting Indian food grain production by Chitikela, Gayathri, Rathod, Santosha, Vijayakumar, S.

“…The study employs interrupted time series and machine learning models, including autoregressive integrated moving average (ARIMA), interrupted ARIMA, artificial neural network (ANN), and interrupted ANN, to forecast key food grains such as rice, wheat, coarse cereals, total cereals, pulses, and total food grains. …”
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Hybridization of process-based models, remote sensing, and machine learning for enhanced spatial predictions of wheat yield and quality by Kheir, Ahmed M.S., Govind, Ajit, Nangia, Vinay, El-Maghraby, Maher A., Elnashar, Abdelrazek, Ahmed, Mukhtar, Aboelsoud, Hesham, Mostafa, Rania, Feike, Til

“…This study aims to improve wheat yield prediction by integrating process-based models (PBM), machine learning (ML), and remote sensing (RS) techniques. …”
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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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Earth observation, open data and machine learning for near real time threat monitoring of vulnerable plant species by Burra, Dharani Dhar, Barua, M.A., Palao, Leo K., Reymondin, Louis

“…Here we report a methodology that monitors threat status of these species in near real time, by deriving data from multiple open data sources, by linking them via a machine learning analytical framework, with interpretations facilitated by a web based geospatial visualization framework.…”
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Using UAV images and phenotypic traits to predict potato morphology and yield in Peru by Ccopi Trucios, Dennis, Ortega Quispe, Kevin, Castañeda Tinco, Italo, Rios Chavarria, Claudia, Enriquez Pinedo, Lucia, Patricio Rosales, Solanch, Ore Aquino, Zoila, Casanova Nuñez Melgar, David, Agurto Piñarreta, Alex Iván, Zúñiga López, Luz Noemí, Urquizo Barrera, Julio

Subjects: “…Machine learning…”
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Comparison of UAV and SAR performance for crop type classification using machine learning algorithms: a case study of humid forest ecology experimental research site of west Africa by Duke, O.P., Alabi, T.R., Neeti, N., Adewopo, Julius

Subjects: “…machine learning…”
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Large-scale rollout of extension training in Bangladesh: Challenges and opportunities for gender-inclusive participation by Medendorp, John William, Reeves, N. Peter, Sal y Rosas Celi, Victor Giancarlo, Harun-Ar-Rashid, Krupnik, Timothy J., Lutomia, Anne Namatsi, Pittendrigh, Barry Robert, Bello-Bravo, Julia

Subjects: “…machine learning…”
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Watershed scale soil moisture estimation model using machine learning and remote sensing in a data-scarce context by Bueno, M., Baca García, C., Montoya, N., Rau, P., Loayza, H.

Subjects: “…machine learning…”
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Drivers of maize yield variability at household level in northern Ghana and Malawi by Gachoki, S., Muthoni, F.K.

Subjects: “…machine learning…”
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Characterization of rice yield based on biomass and SPAD-based leaf nitrogen for large genotype plots by Duque, Andres F., Patino, Diego, Colorado, Julian D., Petro, Eliel E., Rebolledo, Maria C, Mondragon, Iván Fernando, Espinosa, Natalia, Amézquita, Nelson, Puentes, Oscar D, Mendez, Diego, Jaramillo-Botero, Andres

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High-throughput characterization and phenotyping of resistance and tolerance to virus infection in sweetpotato by Kreuze, Jan F., Ramírez, D., Fuentes, S., Loayza, H., Ninanya, J., Rinza, J., David, M., Gamboa, S., Boeck, B. de, Díaz, F., Pérez, A., Silva, L., Campos, Hugo

Subjects: “…machine learning…”
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Aquatic macroinvertebrate image dataset by Koen, R. C. J., Koen, F. J. K.

Subjects: “…machine learning…”
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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 by Balingbing, Carlito B., Kirchner, Sascha, Siebald, Hubertus, Kaufmann, Hans-Hermann, Gummert, Martin, Van Hung, Nguyen, Hensel, Oliver

Subjects: “…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 by 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.

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

Subjects: “…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 by Nantongo, J.S., Serunkuma, E., Burgos, G., Nakitto, M., Kitalikyawe, J., Mendes, T., Davrieux, F., Ssali, R.T.

Subjects: “…machine learning…”
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Deep learning methods improve genomic prediction of wheat breeding by Montesinos-Lopez, Abelardo, Crespo Herrera, Leonardo A., Dreisigacker, Susanna, Gerard, Guillermo S., Vitale, Paolo, Saint Pierre, Carolina, Velu, Govindan, Tarekegn, Zerihun Tadesse, Chavira-Flores, Moisés, Pérez-Rodríguez, Paulino, Ramos-Pulido, Sofía, Lillemo, Morten, Huihui Li, Montesinos-Lopez, Osval ., Crossa, José

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

Subjects: “…machine learning…”
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