Camera settings and biome influence the accuracy of citizen science approaches to camera trap image classification

Scientists are increasingly using volunteer efforts of citizen scientists to classify images captured by motion‐activated trail cameras. The rising popularity of citizen science reflects its potential to engage the public in conservation science and accelerate processing of the large volume of image...

Szczegółowa specyfikacja

Zapisane w:
Opis bibliograficzny
Wydane w:Ecol Evol
Główni autorzy: Egna, Nicole, O'Connor, David, Stacy‐Dawes, Jenna, Tobler, Mathias W., Pilfold, Nicholas, Neilson, Kristin, Simmons, Brooke, Davis, Elizabeth Oneita, Bowler, Mark, Fennessy, Julian, Glikman, Jenny Anne, Larpei, Lexson, Lekalgitele, Jesus, Lekupanai, Ruth, Lekushan, Johnson, Lemingani, Lekuran, Lemirgishan, Joseph, Lenaipa, Daniel, Lenyakopiro, Jonathan, Lesipiti, Ranis Lenalakiti, Lororua, Masenge, Muneza, Arthur, Rabhayo, Sebastian, Ole Ranah, Symon Masiaine, Ruppert, Kirstie, Owen, Megan
Format: Artigo
Język:Inglês
Wydane: John Wiley and Sons Inc. 2020
Hasła przedmiotowe:
Original Research
Dostęp online:https://ncbi.nlm.nih.gov/pmc/articles/PMC7663993/
https://ncbi.nlm.nih.gov/pubmed/33209262
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1002/ece3.6722
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