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20242026
most citedQuantifying the Limits of Segmentation Foundation Models: Modeling Challenges in Segmenting Tree-Like and Low-Contrast Objects

1 citations · 1 across the 4 of their papers we have counts for

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cs.DB2026

Extending GouDa: Generation of Universal Datasets with (and without) Errors for Data Quality Benchmarking

Valerie Restat, André Conrad, Kevin M. Kramer +1

Synthetic data is extremely important in areas such as data quality, data cleaning, and machine learning. It enables the analysis of use cases in which real data is insufficient, u…