Fin Finder app analytics for January 15

Fin Finder is a mobile application that supports customs inspectors in the rapid identification of shark and ray species. The Beta version of this app has achieved a species classification accuracy of 89.4% across an initial set of 35 elasmobranch (shark and ray) species, of which 14 are listed on CITES Appendix II. Initial machine learning models in Fin Finder were developed using over 15,000 photographs of shark fin photos obtained through collaborations with scientific experts, importers in Singapore and international organizations involved in wildlife protection. Future versions of Fin Finder anticipate improvements in species- and genus-level prediction accuracy and support for new species.  Fin Finder is a project managed by the Wild Me Lab (wildme.org) of Conservation X Labs with original support from Microsoft and the Rumah Foundation. The piloting partner is Singapore’s National Parks Board.  Registration will be required prior to use. Please contact finfinder@wildme.org.