Mario Lasseck

Mario.Lasseck@mfn.berlin +49 0 30 889 140 - 8396

Wissenschaftler:in

Ich forsche zu Deep-Learning-Methoden für die Artenerkennung, wobei mein Schwerpunkt auf der akustischen Identifizierung von Tieren liegt.

Projekte

Publikationen

Lasseck, M. (2023). Bird Species Recognition using Convolutional Neural Networks with Attention on Frequency Bands. CEUR Workshop Proceedings, 1-9. URL: https://ceur-ws.org/Vol-3497/paper-175.pdf

æ Sturm, U., Mortega, K.G., Jäckel, D., Darwin, S., Brockmeyer, U., Lasseck, M., Moczek, N., Lehmann, G.U.C., Voigt-Heucke, S.L. (2023). Community engagement and data quality: best practices and lessons learned from a citizen science project on birdsong. Journal of Ornithology, 164(1), 233-244. DOI: https://doi.org/10.1007/s10336-022-02018-8

æ Lasseck, M. (2024). Improving Bird Recognition using Pseudo-Labeled Recordings from the Target Location. Working Notes of the Conference and Labs of the Evaluation Forum (CLEF 2024), 3740, 1-9. URL: https://ceur-ws.org/Vol-3740/paper-199.pdf

æ Wolfgang Wägele, J., Tschan, G.F., Werner, B., Jahn, O., Lasseck, M., Frommolt, K.H. (2024). Bioacoustic data acquisition and species recognition. In Weather stations for biodiversity: a comprehensive approach to an automated and modular monitoring system (119-157). Pensoft Publishers. DOI: https://doi.org/10.3897/ab.e119534

æ Lasseck, M. (2025). Towards Improved Species Identification. Abstract Book [IBAC 25], 7 [S2-1]. URL: https://www.ibac25.com/post/abstract-book

æ Lasseck, M., Eibl, M., Klinck, H., Kahl, S. (2025). BirdNET+ V3.0 model developer preview (Version Number: Preview 1) [Software]. Museum für Naturkunde (MfN) - Leibniz-Institut für Evolutions- und Biodiversitätsforschung. DOI: https://doi.org/10.5281/ZENODO.17571189