An Ecologist-Friendly R Workflow for Expediting Species-Level Classification of Camera Trap Images.

ABSTRACT: Camera trapping has become increasingly common in ecological studies, but is hindered by analyzing large datasets. Recently, artificial intelligence (deep learning models in particular) has emerged as a promising solution. However, applying deep learning for images processing is complex and often requires programming skills in Python, reducing its accessibility. Some authors addressed this issue with user-friendly software, and a further progress was the transposition of deep learning to R, a statistical language frequently used by ecologists, enhancing flexibility and customization of deep learning models without advanced computer expertise. We aimed to develop a user-friendly workflow based on R scripts to streamline the entire process, from selecting to classifying camera trap images. O

SUBMITTER: Petroni L 

PROVIDER: S-EPMC11638126 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature