Biodiversity Information Science and Standards : Conference Abstract
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Corresponding author: Mario Lasseck (mario.lasseck@mfn.berlin)
Received: 14 Jun 2019 | Published: 19 Jun 2019
© 2019 Mario Lasseck
This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Citation: Lasseck M (2019) Augmentation Methods for Biodiversity Training Data. Biodiversity Information Science and Standards 3: e37307. https://doi.org/10.3897/biss.3.37307
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The detection and identification of individual species based on images or audio recordings has shown significant performance increase over the last few years, thanks to recent advances in deep learning. Reliable automatic species recognition provides a promising tool for biodiversity monitoring, research and education. Image-based plant identification, for example, now comes close to the most advanced human expertise (
data augmentation, deep learning, species identification, audio & image recognition
Mario Lasseck
Biodiversity_Next 2019