LNCC
MCTI

Deep Learning applied to Analysis and Synthesis of Biodiversity

Related Areas
  • Applied Ai (AAi)
  • Biodiversity

The availability of information on most organisms is still scarce, making it difficult to use this data in applications for analyzing biodiversity data. We intend to provide methods to intensify data collection by applying deep learning to species identification and remote sensing image analysis. Ecological niche modeling (EMN) uses biodiversity data in conjunction with environmental data to predict the geographic distribution of species. Model-R, developed in a partnership between Jardim Botânico do Rio de Janeiro and LNCC, is a multi-algorithm MNE framework. Recent work has extended MNE approaches to include deep learning techniques, which we intend to incorporate and enhance in Model-R.

Institutions
Data Extreme Lab
Data Extreme Lab