15 citations · 30 across the 6 of their papers we have counts for
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cs.SD2025
Aggregation Strategies for Efficient Annotation of Bioacoustic Sound Events Using Active Learning
Richard Lindholm, Oscar Marklund, Olof Mogren +1
The vast amounts of audio data collected in Sound Event Detection (SED) applications require efficient annotation strategies to enable supervised learning. Manual labeling is expen…
cs.LG2025
The Accuracy Cost of Weakness: A Theoretical Analysis of Fixed-Segment Weak Labeling for Events in Time
John Martinsson, Tuomas Virtanen, Maria Sandsten +1
Accurate labels are critical for deriving robust machine learning models. Labels are used to train supervised learning models and to evaluate most machine learning paradigms. In th…