Abstract
AI-based Identification of Plant Photographs from Herbarium Specimens
Highlights
HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not
Automated plant identification has recently improved significantly due to advances in deep learning and the availability of large amounts of field photos
To advance research on this topic, we built a large dataset that we shared as one of the challenges of the LifeCLEF 2020 (Goëau et al 2020) and 2021 evaluation campaigns ( Goëau et al 2021). It includes more than 320K herbarium specimens collected mostly from the Guiana Shield and the Northern Amazon Rainforest, focusing on about 1K plant species of the French Guiana flora
Summary
HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. Automated plant identification has recently improved significantly due to advances in deep learning and the availability of large amounts of field photos. A key question is whether these digitized specimens could be used to improve the identification performance of species for which we have very few (if any) photos. In addition to this training data, we built a test set for model evaluation, composed of 3,186 field photos collected by two of the best experts on Guyanese flora.
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