Cargando…
A deep semantic vegetation health monitoring platform for citizen science imaging data
Automated monitoring of vegetation health in a landscape is often attributed to calculating values of various vegetation indexes over a period of time. However, such approaches suffer from an inaccurate estimation of vegetational change due to the over-reliance of index values on vegetation’s colour...
Autores principales: | Khan, Asim, Asim, Warda, Ulhaq, Anwaar, Robinson, Randall W. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9328533/ https://www.ncbi.nlm.nih.gov/pubmed/35895741 http://dx.doi.org/10.1371/journal.pone.0270625 |
Ejemplares similares
-
Real-time plant health assessment via implementing cloud-based scalable transfer learning on AWS DeepLens
por: Khan, Asim, et al.
Publicado: (2020) -
How IoT-Driven Citizen Science Coupled with Data Satisficing Can Promote Deep Citizen Science
por: Poslad, Stefan, et al.
Publicado: (2022) -
The benefits of contributing to the citizen science platform iNaturalist as an identifier
por: Callaghan, Corey T., et al.
Publicado: (2022) -
On the impact of Citizen Science-derived data quality on deep learning based classification in marine images
por: Langenkämper, Daniel, et al.
Publicado: (2019) -
Citizen surveillance for environmental monitoring: combining the efforts of citizen science and crowdsourcing in a quantitative data framework
por: Welvaert, Marijke, et al.
Publicado: (2016)