Author

S. Morandage

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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Plant Biology· 2

Signature Assays, Organisms & Methods

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Research Focus:cell type annotation· 2 Approach:deep learning· 2 Research Focus:clustering· 1 Assay:imaging· 1 Approach:statistical model· 1 Research Focus:trajectory inference· 1

Frequent Co-Authors

A. Schnepf· 2 shared G. Lobet· 2 shared H. Vereecken· 2 shared J. Vanderborght· 2 shared C. Sheng· 1 shared D. Leitner· 1 shared F. Bauer· 1 shared L. Laerm· 1 shared

Activity by Year

2017-2021 · peak 1/yr

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10 top collaborators · 37 mutual co-author links

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2 shared papersPlant Biology

A. Schnepf

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2 papers

Recent·Most cited

Combining deep learning and automated feature extraction to analyze minirhizotron images: development and validation of a new pipeline

F. Bauer, L. Laerm, S. Morandage, G. Lobet, J. Vanderborght, H. Vereecken, A. Schnepf

This paper develops and validates a pipeline combining deep learning and automated feature extraction to analyze minirhizotron images, showing high accuracy and significantly faster processing than manual methods.

bioRxiv · Dec 1, 2021 · PreprintPlant Biology

CRootBox: A Structural-Functional Modelling Framework For Root Systems

A. Schnepf, D. Leitner, M. Landl, G. Lobet, T. H. Mai, S. Morandage, C. Sheng, M. Zoerner, J. Vanderborght, H. Vereecken

CRootBox is a root architecture model that simulates root growth and interactions with soil environments, demonstrating its use in various scenarios including field-scale simulations and coupling with soil physics.

bioRxiv · May 19, 2017Plant Biology