Fared Farag
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Graduate Research Assistant
Graduate Student Researcher
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Biography and Research Information
OverviewAI-generated summary
Fared Farag is a researcher whose work focuses on applying manifold and spatiotemporal learning techniques to multispectral unoccupied aerial system (UAS) imagery for phenotype prediction. His research has involved characterizing rice nitrogen use phenotypes from multitemporal UAV imagery using manifold learning, as presented at the NAPPN Annual Conference. Farag has also contributed to the development of open-source tools, including a Python package for FAO-56 evapotranspiration calculations.
His scholarly output includes three publications, with a total of six citations and an h-index of 2. Farag collaborates with researchers at Arkansas State University, including Ahmed A. Hashem (three shared publications), Emily S. Bellis (two shared publications), and Jason Causey (one shared publication). He remains actively engaged in research, with his most recent publication in 2024.
Metrics
- h-index: 2
- Publications: 3
- Citations: 8
Selected Publications
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Manifold and spatiotemporal learning on multispectral unoccupied aerial system imagery for phenotype prediction (2024)
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“Version 1.3.0 pyfao56: FAO-56 evapotranspiration in Python” (2024)
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NAPPN Annual Conference Abstract: Characterizing Rice Nitrogen Use Phenotypes from Multitemporal UAV Imagery with Manifold Learning (2022)
Collaboration Network
Top Collaborators
- “Version 1.3.0 pyfao56: FAO-56 evapotranspiration in Python”
- Manifold and spatiotemporal learning on multispectral unoccupied aerial system imagery for phenotype prediction
- NAPPN Annual Conference Abstract: Characterizing Rice Nitrogen Use Phenotypes from Multitemporal UAV Imagery with Manifold Learning
- Manifold and spatiotemporal learning on multispectral unoccupied aerial system imagery for phenotype prediction
- NAPPN Annual Conference Abstract: Characterizing Rice Nitrogen Use Phenotypes from Multitemporal UAV Imagery with Manifold Learning
- “Version 1.3.0 pyfao56: FAO-56 evapotranspiration in Python”
- “Version 1.3.0 pyfao56: FAO-56 evapotranspiration in Python”
- “Version 1.3.0 pyfao56: FAO-56 evapotranspiration in Python”
- “Version 1.3.0 pyfao56: FAO-56 evapotranspiration in Python”
- “Version 1.3.0 pyfao56: FAO-56 evapotranspiration in Python”
- “Version 1.3.0 pyfao56: FAO-56 evapotranspiration in Python”
- “Version 1.3.0 pyfao56: FAO-56 evapotranspiration in Python”
- “Version 1.3.0 pyfao56: FAO-56 evapotranspiration in Python”
- Manifold and spatiotemporal learning on multispectral unoccupied aerial system imagery for phenotype prediction
- Manifold and spatiotemporal learning on multispectral unoccupied aerial system imagery for phenotype prediction
- Manifold and spatiotemporal learning on multispectral unoccupied aerial system imagery for phenotype prediction
- Manifold and spatiotemporal learning on multispectral unoccupied aerial system imagery for phenotype prediction
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