Author

T. Pridmore

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 Research Focus:clustering· 2 Approach:deep learning· 2 Assay:imaging· 2 Organism:plant (other)· 2 Research Focus:spatial domain detection· 1 Approach:transformer / foundation model· 1

Frequent Co-Authors

A. French· 2 shared M. Pound· 2 shared R. Yasrab· 2 shared

Activity by Year

2020-2020 · peak 2/yr

Co-Author Collaboration Network

3 top collaborators · 3 mutual co-author links

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2 shared papersPlant Biology

A. French

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2 papers

Recent·Most cited

PhenomNet: Bridging Phenotype-Genotype Gap: A CNN-LSTM Based Automatic Plant Root Anatomization System.

R. Yasrab, M. Pound, A. French, T. Pridmore

PhenomNet is a CNN-LSTM system that segments plant roots and classifies accessions, achieving high accuracy in phenotype and genotype analysis.

bioRxiv · May 3, 2020 · PreprintPlant Biology

RootNet: A Convolutional Neural Networks for Complex Plant Root Phenotyping from High-Definition Datasets

R. Yasrab, M. Pound, A. French, T. Pridmore

RootNet is a CNN model for high-accuracy root segmentation in plant phenotyping, designed to handle thin roots and high-resolution images using a patch-based training approach.

bioRxiv · May 1, 2020 · PreprintPlant Biology