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Towards Context-Rich Automated Biodiversity Assessments: Deriving AI-Powered Insights from Camera Trap Data.

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第一作者： Paul,Fergus

第一单位： School of Computer Science and Mathematics, Liverpool John Moores University, James Parsons Building, Byrom Street, Liverpool L3 3AF, UK.

作者： Paul,Fergus ^[1] ; Carl,Chalmers ^[1] ; Naomi,Matthews ^[2] ; Stuart,Nixon ^[2] ; André,Burger ^[3] ; Oliver,Hartley ^[4] ; Chris,Sutherland ^[4] ; Xavier,Lambin ^[5] ; Steven,Longmore ^[6] ; Serge,Wich ^[7]

作者单位： School of Computer Science and Mathematics, Liverpool John Moores University, James Parsons Building, Byrom Street, Liverpool L3 3AF, UK. ^[1] Chester Zoo, Upton-by-Chester, Chester CH2 IEU, UK. ^[2] Welgevonden Game Reserve, P.O. Box 433, Vaalwater 0530, South Africa. ^[3] School of Mathematics and Statistics, Mathematical Institute, University of St Andrews, North Haugh, St Andrews KY16 9SS, UK. ^[4] School of Biological Sciences, University of Aberdeen, Tillydrone Avenue, Aberdeen AB24 2TZ, UK. ^[5] Astrophysics Research Institute, Liverpool John Moores University, IC2, Liverpool Science Park, 146 Brownlow Hill, Liverpool L3 5RF, UK. ^[6] School of Biological and Environmental Sciences, Liverpool John Moores University, James Parsons Building, Byrom Street, Liverpool L3 3AF, UK. ^[7]

关键词 biodiversity monitoring deep learning large language models object detection vision transformers wildlife conservation