Revisiting giraffe photo-identification using deep learning and network analysis
An increasing number of research programs rely on photographic capture-recapture (vs. direct marking) of individuals to study distribution and demography within animal populations. Photo-identification of individuals living in the wild is sometimes feasible using idiosyncratic coat or skin patterns, like for giraffes. When performed manually, the task is tedious and becomes almost impossible as populations […]
A computer-assisted system for photographic mark–recapture analysis
Photographic mark–recapture is a cost-effective, non-invasive way to study populations. However, to efficiently apply photographic mark–recapture to large populations, computer software is needed for image manipulation and pattern matching. We created an open-source application for the storage, pattern extraction and pattern matching of digital images for the purposes of mark–recapture analysis. The resulting software package […]