Resultados de búsqueda - "Python"

CGIAR Climate Change Synthesis Scripts por Orth, Alan S.

Materias: “…python…”
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PyRice: a Python package for querying Oryza sativa databases por CGIAR Research Program on Rice

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Web-Based Biobank System Infrastructure Monitoring Using Python, Perl, and PHP por Norling, Martin, Kihara, Absolomon, Kemp, Stephen J.

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

Materias: “…Python…”
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Garrapatas exóticas: hallazgo de Amblyomma latum Koch, 1844 (Acari: Ixodidae) parasitando Python regius (Serpentes: Boidae) en Uruguay por Venzal, José Manuel, Nava, Santiago, Guglielmone, Alberto

Materias: “…Pythons…”
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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

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Python Climate Predictability Tool (PyCPT) training for improved seasonal climate prediction over Ethiopia por Ahmed, Jemal Seid, Teshome, Asaminew, Demissie, Teferi Dejene

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An FAO model comparison: Python Agroecological Zoning (PyAEZ) and AquaCrop to assess climate change impacts on crop yields in Nepal por Alvar-Beltran, J., Soldan, R., Vanuytrecht, E., Heureux, A., Shrestha, Nirman, Manzanas, R., Pant, K. P., Franceschini, G.

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Dynamic Research EvaluAtion for Management, Python version (DREAMpy): open source software for evaluating the economic impacts of agricultural research and development projects por CGIAR Research Program on Policies, Institutions, and Markets

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Training for Climate Data Analysis and Visualization por Mersha, Yonas, Demissie, Teferi Dejene

“…The objective of the Python training for climate data analysis and visualization was to equip the participants with the necessary knowledge and skills required for processing, analyzing, and visualizing climate data using Python. …”
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A Comprehensive Database of CGIAR Climate-Related Journal Articles (2012–2023) por Orth, Alan S., Bosire, Caroline K., Rabago, Laura, Vaidya, Shrijana, Rajbhandari, Sitashma, Pradhan, Prajal, Mukherji, Aditi

“…The metadata was retrieved from eight CGIAR institutional repositories, processed using a Python-based extract, transform, and load (ETL) pipeline, and screened for climate change relevance in Rayyan. …”
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Auto-CCAFS-MOT: a batch calculator tool for farmers greenhouse gas emissions (GHG) por CGIAR Platform for Big Data in Agriculture

“…Leveraging on the CCAFS-MOT version, we developed a new system to calculate GHG emissions for multiple crop events. It was completed in python to facilitate the integration with web applications. …”
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Auto-CCAFS-MOT: a batch calculator tool for farmers GHG emissions por CGIAR Research Program on Climate Change, Agriculture and Food Security

“…This new development was completed on python that facilitates its integration with web applications. …”
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BrRacemeCounter: Mask R-CNN for Raceme Instance Segmentation por International Center for Tropical Agriculture (CIAT) Tropical Forages Program, Arrechea-Castillo, Darwin Alexis, Cardoso Arango, Juan Andres

“…This is an adapted implementation of Mask R-CNN on Python 3, Keras, and TensorFlow. The model generates bounding boxes and segmentation masks for each instance of an object in the image. …”
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Data Library Maintenance and Maproom Development Training with Zambia Meteorology Department por Rose, Alison

“…A staff member from the International Research Institute for Climate and Society travelled to Zambia to train the Zambia Met on how to use the Python Maprooms from October 22 – November 5, 2022.…”
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Clim2Agri version 1.0 por Montes, Carlo, Gómez, Francisco

“…Clim2Agri is a set of data processing tools (Clim2Agri) that allow the agricultural research and development community to simply and efficiently access data from open access platforms to be used in applications such as modeling or analysis of observations was generated. Clim2Agri is a Python-based application allowing the extraction and subsetting of agriculturally-relevant climate and land surface data from multiple gridded products (e.g., atmospheric reanalysis, satellite-derived products), from multiple formats (e.g., netCDF4, HDF), and their transformation into formats that are required by the agriculture research and crop modeling community (e.g., csv, txt).…”
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NEXUS Gains Talk 11: Integrating Water Resources Management in a Shared River Basin por Velpuri, Naga Manohar, Etichia, Mikiyas, Lautze, Jonathan F.

“…NEXUS Gains has partnered with INMACOM and the University of Manchester to build a robust and comprehensive river basin systems model using an open-source Python water resources (Pywr) framework that accounts for water demands from agriculture, domestic, industry, and energy sectors. …”
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Endogenous hepadnaviruses, bornaviruses and circoviruses in snakes por Gilbert, C., Meik, J.M., Dashevsky, D., Card, D.C., Castoe, T.A., Schaack, Sarah

“…Cross-species PCR screening of orthologous loci and computational scanning of the python and king cobra genomes reveals that circoviruses integrated most recently (within the last approx. 10 Myr), whereas bornaviruses and hepadnaviruses integrated at least approximately 13 and approximately 50 Ma, respectively. …”
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Actualización hacia el sistema e-Agrology 360 por Gardeazabal Monsalve, Andrea, Núñez Jimenez, Daniel

“…El sistema, desarrollado con tecnologías open source como JavaScript, Python y Flutter, sigue un modelo de integración continua que permite actualizaciones frecuentes. …”
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West Africa Regional Training On the Improved NextGen Seasonal Forecasting Approach (PyCPT 2) por Grossi, Amanda, Robertson, Andrew, Trzaska, Sylwia, Dinku, Tufa, Zougmoré, Robert B., Minoungou, Bernard, Mohamed, Hamatan

“…In particular, the major objectives of the training were to strengthen the knowledge and understanding of national meteorological services of seasonal forecasting tools, introduce the new advances and functionalities of the Python (PyCPT2) interface for the NextGen forecasting approach, configure and run PyCPT version 2 to make the best- available forecasts in participants’ home countries, including forecast verification, and provide foundational training on best practices for forecast communication including the flexible forecast format.…”
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