Species Identification: Difference between revisions
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{{Disclaimer}}
Machine learning tools are increasingly being used to help in the identification of organisms, both from photographic documentation and (in cases such as birds) audio recordings. These tools are deployed in personal apps and as part of citizen science projects<ref>{{Cite web|url=https://www.plantsnap.com/|title=PlantSnap - Plant Identifier App, #1 Mobile App for Plant Identification|website=www.plantsnap.com|access-date=2021-03-09}}</ref><ref>{{Cite web|url=https://apps.apple.com/us/app/fieldguide-for-everything/id879829383|title=Fieldguide – for everything|website=App Store|language=en-us|access-date=2021-03-09}}</ref><ref>{{Cite web|url=https://birdnet.cornell.edu/|title=BirdNET – The easiest way to identify birds by sound.|language=en-US|access-date=2021-03-09}}</ref><ref>{{Cite web|url=https://www.inaturalist.org/pages/seek_app|title=Seek by iNaturalist · iNaturalist|website=iNaturalist|language=en|access-date=2021-03-09}}</ref>, as well as within formal scientific monitoring efforts.
==Background Readings==
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==Libraries and Tools==
==Data==
*'''FGVC7 Competitions:''' A set of competitions/datasets held as part of CVPR 2020, available [https://sites.google.com/view/fgvc7/competitions?authuser=0 here].
*'''LifeClef 2020:''' A set of competitions/datasets, available [https://www.imageclef.org/LifeCLEF2020 here].
*'''Camera Trap ML Survey''': An overview of datasets used in current camera trap machine learning projects, available [https://agentmorris.github.io/camera-trap-ml-survey/ here].
==Future Directions==
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