Andreas Maier

A standardized evaluation framework reveals that even near-perfect machine learning scores in power system protection can be misleading without consistent assessment criteria.

Fine-tuning Whisper models for multilingual medical ASR reveals that the best performance hinges on the adaptation strategy, with surprising shifts in internal representations based on language context.

PhonoQ-derived features boost phonological classification accuracy, revealing intricate speech patterns that traditional models miss.

DITL redefines mammography classification by seamlessly integrating dataset characteristics, achieving unprecedented performance across diverse data scales.