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Image-based taxonomic classification of bulk biodiversity samples using deep learning and domain adaptation
View ORCID ProfileTomochika Fujisawa, View ORCID ProfileVíctor Noguerales, View ORCID ProfileEmmanouil Meramveliotakis, View ORCID ProfileAnna Papadopoulou, View ORCID ProfileAlfried P. Vogler
doi: https://doi.org/10.1101/2021.12.22.473797
Tomochika Fujisawa
1The Center for Data Science Education and Research, Shiga University, 1-1-1 Banba, Hikone, Shiga 522-8522, Japan
Víctor Noguerales
2Department of Biological Sciences, University of Cyprus, PO Box 20537, Nicosia 1678, Cyprus
3Instituto de Productos Naturales y Agrobiología (IPNA-CSIC), Astrofísico Francisco Sánchez 3, 38206, San Cristóbal de La Laguna, Tenerife, Canary Islands, Spain
Emmanouil Meramveliotakis
2Department of Biological Sciences, University of Cyprus, PO Box 20537, Nicosia 1678, Cyprus
Anna Papadopoulou
2Department of Biological Sciences, University of Cyprus, PO Box 20537, Nicosia 1678, Cyprus
Alfried P. Vogler
4Department of Life Sciences, Natural History Museum, Cromwell Rd, London, SW7 5BD, UK
5Department of Life Sciences, Silwood Park Campus, Imperial College London, Ascot, SL5 7PY, UK

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Posted December 23, 2021.
Image-based taxonomic classification of bulk biodiversity samples using deep learning and domain adaptation
Tomochika Fujisawa, Víctor Noguerales, Emmanouil Meramveliotakis, Anna Papadopoulou, Alfried P. Vogler
bioRxiv 2021.12.22.473797; doi: https://doi.org/10.1101/2021.12.22.473797
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