Technology has an important part to play in wildlife and ecosystem conservation, and can
vastly reduce time and effort spent in the associated tasks. Deep learning methods for …

Animal biometrics is a frontier area of computer vision, pattern recognition and cognitive
science to plays the vital role for the registration, unique identification, and verification of …

Artificial intelligence (AI) and machine learning (ML) present revolutionary opportunities to
enhance our understanding of animal behaviour and conservation strategies. Using …

Monitoring of protected areas to curb illegal activities like poaching and animal trafficking is
a monumental task. To augment existing manual patrolling efforts, unmanned aerial …

This paper describes and explains design patterns for software that supports how analysts
can efficiently inspect and classify camera trap images for wildlife‐related ecological …

As a highly endangered species, the giant panda (panda) has attracted significant attention
in the past decades. Considerable efforts have been put on panda conservation and …

Photo-identification of individual snow leopards (Panthera uncia) is the primary data source
for density estimation via capture-recapture statistical methods. To identify individual snow …

Individual identification contributes significantly towards investigating behavioral
mechanisms of animals and understanding underlying ecological principles. Most studies …

Camera‐traps are valuable tools for estimating wildlife population density, and recently
developed models enable density estimation without the need for individual recognition …

African elephants are vital to their ecosystems, but their populations are threatened by a rise
in human-elephant conflict and poaching. Monitoring population dynamics is essential in …