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Deep learning enables satellite-based monitoring of large populations of terrestrial mammals across heterogeneous landscape.
Wu, Zijing; Zhang, Ce; Gu, Xiaowei; Duporge, Isla; Hughey, Lacey F; Stabach, Jared A; Skidmore, Andrew K; Hopcraft, J Grant C; Lee, Stephen J; Atkinson, Peter M; McCauley, Douglas J; Lamprey, Richard; Ngene, Shadrack; Wang, Tiejun.
Afiliação
  • Wu Z; Department of Natural Resources, Faculty of Geo-Information Science and Earth Observation, University of Twente, Enschede, The Netherlands.
  • Zhang C; Lancaster Environment Center, Lancaster University, Lancaster, UK.
  • Gu X; UK Centre for Ecology & Hydrology, Lancaster, UK.
  • Duporge I; School of Computing, University of Kent, Canterbury, UK.
  • Hughey LF; Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA.
  • Stabach JA; U.S. Army Research Laboratory, Army Research Office, Durham, NC, USA.
  • Skidmore AK; The National Academies of Sciences, Washington, D.C., USA.
  • Hopcraft JGC; Conservation Ecology Center, Smithsonian National Zoo and Conservation Biology Institute, Front Royal, VA, USA.
  • Lee SJ; Conservation Ecology Center, Smithsonian National Zoo and Conservation Biology Institute, Front Royal, VA, USA.
  • Atkinson PM; Department of Natural Resources, Faculty of Geo-Information Science and Earth Observation, University of Twente, Enschede, The Netherlands.
  • McCauley DJ; School of Natural Sciences, Macquarie University, Sydney, NSW, Australia.
  • Lamprey R; Institute of Biodiversity, Animal Health, and Comparative Medicine, University of Glasgow, Glasgow, UK.
  • Ngene S; U.S. Army Research Laboratory, Army Research Office, Durham, NC, USA.
  • Wang T; Lancaster Environment Center, Lancaster University, Lancaster, UK.
Nat Commun ; 14(1): 3072, 2023 05 27.
Article em En | MEDLINE | ID: mdl-37244940
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Ecossistema / Aprendizado Profundo Limite: Animals Idioma: En Revista: Nat Commun Assunto da revista: BIOLOGIA / CIENCIA Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Holanda
Texto completo
Adicionar na Minha BVS
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Ecossistema / Aprendizado Profundo Limite: Animals Idioma: En Revista: Nat Commun Assunto da revista: BIOLOGIA / CIENCIA Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Holanda