2 citations · 4 across the 4 of their papers we have counts for
5 papers
Enumerating the k-fold configurations in multi-class classification problems
Attila Fazekas, Gyorgy Kovacs
K-fold cross-validation is a widely used tool for assessing classifier performance. The reproducibility crisis faced by artificial intelligence partly results from the irreproducib…
mlscorecheck: Testing the consistency of reported performance scores and experiments in machine learning
György Kovács, Attila Fazekas
Addressing the reproducibility crisis in artificial intelligence through the validation of reported experimental results is a challenging task. It necessitates either the reimpleme…
Testing the Consistency of Performance Scores Reported for Binary Classification Problems
Attila Fazekas, György Kovács
Binary classification is a fundamental task in machine learning, with applications spanning various scientific domains. Whether scientists are conducting fundamental research or re…
A new baseline for retinal vessel segmentation: Numerical identification and correction of methodological inconsistencies affecting 100+ papers
György Kovács, Attila Fazekas
In the last 15 years, the segmentation of vessels in retinal images has become an intensively researched problem in medical imaging, with hundreds of algorithms published. One of t…
Approximately Optimal Binning for the Piecewise Constant Approximation of the Normalized Unexplained Variance (nUV) Dissimilarity Measure
Attila Fazekas, György Kovács
The recently introduced Matching by Tone Mapping (MTM) dissimilarity measure enables template matching under smooth non-linear distortions and also has a well-established mathemati…