Please use this identifier to cite or link to this item: 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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