activity
20232026
most citedGeneralization in birdsong classification: impact of transfer learning methods and dataset characteristics

4 citations · 4 across the 7 of their papers we have counts for

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5 papers · 1 filter

cs.LG2026

Effects of interpulse-interval variation on deep-learning classification of bat vocalizations

Welmoed R. Eversteijn, Burooj Ghani, A. Leonie Baier +1

Temporal context may aid automated bat-species classification, but the contribution of specific features remains unclear. We investigated whether variation in the interpulse interv…

cs.LG2026

ChiroEcho: extending automated bat vocalisation classification beyond the learned taxonomy

Burooj Ghani, Welmoed Eversteijn, Milan van Hirtum +4

Bats are key indicators of ecosystem health and are protected throughout Europe, making reliable population monitoring a conservation priority. Their cryptic nocturnal lifestyle ma…

cs.LG2026

Torus embeddings

Dan Stowell

Many data representations are vectors of continuous values. In particular, deep learning embeddings are data-driven representations, typically either unconstrained in Euclidean spa…

cs.LG2025

Clustering and novel class recognition: evaluating bioacoustic deep learning feature extractors

Vincent S. Kather, Burooj Ghani, Dan Stowell

In computational bioacoustics, deep learning models are composed of feature extractors and classifiers. The feature extractors generate vector representations of the input sound se…

cs.LG2023

Auto deep learning for bioacoustic signals

Giulio Tosato, Abdelrahman Shehata, Joshua Janssen +3

This study investigates the potential of automated deep learning to enhance the accuracy and efficiency of multi-class classification of bird vocalizations, compared against tradit…