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Community engagement and data quality: best practices and lessons learned from a citizen science project on birdsong.

Autor: Jäckel, Denise, Mortega, Kim G., Darwin, Sarah, Brockmeyer, Ulrich, Sturm, Ulrike, Lasseck, Mario, Moczek, Nicola, Lehmann, Gerlind U. C., Voigt-Heucke, Silke L.

Publikováno v: Journal of Ornithology; Jan2023, Vol. 164 Issue 1, p233-244, 12p

Plant Identification: Experts vs. Machines in the Era of Deep Learning: Deep learning techniques challenge flora experts

Autor: Bonnet, Pierre, Goëau, Hervé, Hang, Siang, Lasseck, Mario, Sulc, Milaň, Malécot, Valéry, Jauzein, Philippe, Melet, Jean-Claude, You, Christian, Joly, Alexis

Publikováno v: Multimedia Tools and Applications for Environmental & Biodiversity Informatics
Multimedia Tools and Applications for Environmental & Biodiversity Informatics, Chapter 8, pp.131-149, 2018, 978-3-319-76444-3. ⟨10.1007/978-3-319-76445-0_8⟩
Multimedia Tools and Applications for Environmental & Biodiversity Informatics, Chapter 8, Editions Springer, pp.131-149, 2018, Multimedia Systems and Applications Series, 978-3-319-76444-3. ⟨10.1007/978-3-319-76445-0_8⟩
Multimedia tools and applications for environmental and biodiversity informatics.

International audience; Automated identification of plants and animals have improved considerably in the last few years, in particular thanks to the recent advances in deep learning. The next big question is how far such automated systems are from th

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::1ad5c1524539e920f3e0276671092a10
https://hal.archives-ouvertes.fr/hal-01913277/document

Towards Automatic Large-Scale Identification of Birds in Audio Recordings.

Autor: Lasseck, Mario

Publikováno v: Experimental Ir Meets Multilinguality, Multimodality & Interaction; 2015, p364-375, 12p

Augmentation Methods for Biodiversity Training Data.

Autor: Lasseck, Mario

Publikováno v: Biodiversity Information Science & Standards; 2019, p1-2, 2p