Deep learning is driving recent advances behind many everyday technologies, including
speech and image recognition, natural language processing and autonomous driving. It is …

Camera trap** is an effective non-invasive method for collecting data on wildlife species
to address questions of ecological and conservation interest. We reviewed 2,167 camera …

Real world data often have a long-tailed and open-ended distribution. A practical
recognition system must classify among majority and minority classes, generalize from a few …

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 …

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

Satellites allow large‐scale surveys to be conducted in short time periods with repeat
surveys possible at intervals of< 24 h. Very‐high‐resolution satellite imagery has been …

Camera traps deployed in remote locations provide an effective method for ecologists to
monitor and study wildlife in a non-invasive way. However, current camera traps suffer from …

Emerging technologies support a new era of applied wildlife research, generating data on
scales from individuals to populations. Computer vision methods can process large datasets …

As the capacity to collect and store large amounts of data expands, identifying and
evaluating strategies to efficiently convert raw data into meaningful information is …

Camera trap** is increasingly being used to monitor wildlife, but this technology typically
requires extensive data annotation. Recently, deep learning has substantially advanced …