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Mikolaj Cieslak

2 papers indexed

arxivcs.CV2026-07-20

Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data

Samy Mounir, Mikolaj Cieslak, Najmeddine Dhieb, Hakim Ghazzai, Jonathan Klein, Katja Froehlich, et al.

Vision-based automation is an excellent candidate for reducing manual labor in greenhouse crop production and phenotyping. However, progress is constrained by the lack of annotated training data. Recent advances in vision-based foundational models have shown promising results in…

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arxivcs.CV2026-07-10

The Effects of Synthetic Data and Label Distribution on Canola Branch Counting

Amirsalar Darvishpour, Mikolaj Cieslak, Adam Runions

Collecting annotated plant images for automated phenotyping is often slow and expensive. Plant models simulating growth and development can generate unlimited synthetic images with exact labels. However, previous work has established that whether incorporating synthetic data impr…

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