Cargando…
Protecting endangered megafauna through AI analysis of drone images in a low-connectivity setting: a case study from Namibia
Assessing the numbers and distribution of at-risk megafauna such as the black rhino (Diceros bicornis) is key to effective conservation, yet such data are difficult to obtain. Many current monitoring technologies are invasive to the target animals and expensive. Satellite monitoring is emerging as a...
Autores principales: | Hua, Alice, Martin, Kevin, Shen, Yuzeng, Chen, Nicole, Mou, Catherine, Sterk, Maximilian, Reinhard, Berend, Reinhard, Friedrich F., Lee, Stephen, Alibhai, Sky, Jewell, Zoe C. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9356584/ https://www.ncbi.nlm.nih.gov/pubmed/35942123 http://dx.doi.org/10.7717/peerj.13779 |
Ejemplares similares
-
Monitoring rhinoceroses in Namibia’s private custodianship properties
por: Jewell, Zoe C., et al.
Publicado: (2020) -
Determining the numbers of a landscape architect species (Tapirus terrestris), using footprints
por: Moreira, Danielle O., et al.
Publicado: (2018) -
Leveraging social media and deep learning to detect rare megafauna in video surveys
por: Mannocci, Laura, et al.
Publicado: (2021) -
Is droning on making life unbearable?
por: Schwieterman, Gail D
Publicado: (2019) -
Cheetahs (Acinonyx jubatus) running the gauntlet: an evaluation of translocations into free-range environments in Namibia
por: Weise, Florian J., et al.
Publicado: (2015)