Author

Tivadar Danka

HUN-REN Szegedi Biológiai Kutatóközpont

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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Bioinformatics· 2

Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Assay:imaging· 2 Organism:Arabidopsis· 1 Research Focus:benchmarking· 1 Research Focus:cell type annotation· 1

Frequent Co-Authors

Péter HorváthiD· 2 shared Ábel SzkalisityiD· 1 shared Allen GoodmaniD· 1 shared András KristoniD· 1 shared András VicziániD· 1 shared Anne Elizabeth CarpenteriD· 1 shared Árpád Bálind· 1 shared Botond Mathe· 1 shared

Activity by Year

2019-2020 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 37 mutual co-author links

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2 shared papersBioinformatics

Péter HorváthORCID

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2 papers

Recent·Most cited

A deep learning framework for nucleus segmentation using image style transfer

Réka Hollandi, Ábel Szkalisity, Tímea Tóth, Ervin Tasnádi, Csaba Molnár, Botond Mathe, István Grexa, József Molnár, Árpád Bálind, Mate Gorbe, Mária Kovács, Ede Migh, Allen Goodman, Tamás Balassa, Krisztián Koós, , Péter Horváth

The paper introduces a deep learning framework for nucleus segmentation that uses image style transfer to adapt to new data without expert annotations, outperforming existing methods on diverse microscopy images.

Cell Systems · May 1, 2020Peer-reviewedBioinformatics

A deep learning-based approach for high-throughput hypocotyl phenotyping

Orsolya Dobos, Péter Horváth, Ferenc Nagy, Tivadar Danka, András Viczián

A deep learning-based algorithm provides an adaptable tool for determining hypocotyl or coleoptile length across different plant species.

PLANT PHYSIOLOGY · Oct 21, 2019Peer-reviewedBioinformatics