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https://hdl.handle.net/10316/114559
Title: | Envisaging a global infrastructure to exploit the potential of digitised collections | Authors: | Groom, Quentin Dillen, Mathias Addink, Wouter Ariño, Arturo H H Bölling, Christian Bonnet, Pierre Cecchi, Lorenzo Ellwood, Elizabeth R Figueira, Rui Gagnier, Pierre-Yves Grace, Olwen M Güntsch, Anton Hardy, Helen Huybrechts, Pieter Hyam, Roger Joly, Alexis A J Kommineni, Vamsi Krishna Larridon, Isabel Livermore, Laurence Lopes, Ricardo Jorge Meeus, Sofie Miller, Jeremy A Milleville, Kenzo Panda, Renato Pignal, Marc Poelen, Jorrit Ristevski, Blagoj Robertson, Tim Rufino, Ana C. Santos, Joaquim Schermer, Maarten Scott, Ben Seltmann, Katja Chantre Teixeira, Heliana Trekels, Maarten Gaikwad, Jitendra |
Keywords: | biodiversity; computer vision; functional traits; machine learning; species identification; specimens | Issue Date: | 2023 | Volume: | 11 | Abstract: | Tens of millions of images from biological collections have become available online over the last two decades. In parallel, there has been a dramatic increase in the capabilities of image analysis technologies, especially those involving machine learning and computer vision. While image analysis has become mainstream in consumer applications, it is still used only on an artisanal basis in the biological collections community, largely because the image corpora are dispersed. Yet, there is massive untapped potential for novel applications and research if images of collection objects could be made accessible in a single corpus. In this paper, we make the case for infrastructure that could support image analysis of collection objects. We show that such infrastructure is entirely feasible and well worth investing in. | URI: | https://hdl.handle.net/10316/114559 | ISSN: | 1314-2828 | DOI: | 10.3897/BDJ.11.e109439 | Rights: | openAccess |
Appears in Collections: | I&D CISUC - Artigos em Revistas Internacionais |
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Groom et al. - 2023 - Envisaging a global infrastructure to exploit the potential of digitised collections.pdf | 1.11 MB | Adobe PDF | View/Open |
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