Author

E. J. Forrestel

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Pathology· 1 Plant Biology· 1

Signature Assays, Organisms & Methods

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Assay:imaging· 2 Research Focus:clustering· 1 Approach:deep learning· 1 Research Focus:differential expression· 1 Research Focus:dimensionality reduction· 1 Approach:machine learning (classical)· 1 Organism:plant (other)· 1 Research Focus:software / tool· 1

Frequent Co-Authors

A. McElrone· 1 shared C. R. Brodersen· 1 shared D. Sousa· 1 shared F. E. Romero Galvan· 1 shared G. R. Trolley· 1 shared G. Theroux-Rancourt· 1 shared J. M. Earles· 1 shared K. M. Gold· 1 shared

Activity by Year

2020-2022 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 20 mutual co-author links

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1 shared paperPlant Biology

A. McElrone

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2 papers

Recent·Most cited

Scalable early detection of grapevine virus infection with airborne imaging spectroscopy

F. E. Romero Galvan, D. Sousa, R. Pavlick, S. Aggarwal, G. R. Trolley, E. J. Forrestel, S. L. Bolton, N. Dokoozlian, M. D. M. Alsina, K. M. Gold

This paper uses airborne imaging spectroscopy and machine learning to detect GLRaV-3 infection in grapevines during the latent, asymptomatic phase, achieving high accuracy at 3-meter resolution.

bioRxiv · Oct 4, 2022Pathology

Digitally Deconstructing Leaves in 3D Using X-ray Microcomputed Tomography and Machine Learning

G. Theroux-Rancourt, M. R. Jenkins, C. R. Brodersen, A. McElrone, E. J. Forrestel, J. M. Earles

This paper introduces a machine learning pipeline to automate 3D leaf segmentation from microCT scans, significantly reducing processing time and improving scalability for plant phenotyping.

bioRxiv · Apr 4, 2020Plant Biology