Accurate identification of animal species is necessary to understand biodiversity richness,
monitor endangered species, and study the impact of climate change on species distribution …

A typical camera trap survey may produce millions of images that require slow, expensive
manual review. Consequently, critical conservation questions may be answered too slowly …

The implementation of intelligent software to identify and classify objects and individuals in
visual fields is a technology of growing importance to operatives in many fields, including …

The use of camera traps is a nonintrusive monitoring method to obtain valuable information
about the appearance and behavior of wild animals. However, each study generates …

Deep learning (DL) algorithms are the state of the art in automated classification of wildlife
camera trap images. The challenge is that the ecologist cannot know in advance how many …

Simple Summary The imagery captured by cameras provides important information for
wildlife research and conservation. Deep learning technology can assist ecologists in …

Non-intrusive monitoring of animals in the wild is possible using camera trapping networks.
The cameras are triggered by sensors in order to disturb the animals as little as possible …

Simple Summary Camera traps, also known as “game cameras” or “trail cameras”, have
increasingly been used in wildlife research over the last 20 years. Although early units were …

The ability of a researcher to re‐identify (re‐ID) an individual animal upon re‐encounter is
fundamental for addressing a broad range of questions in the study of ecosystem function …

Camera traps are increasingly used to answer complex ecological questions. However, the
rapidly growing number of images collected presents technical challenges. Each image …