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

Camera traps have quickly transformed the way in which many ecologists study the
distribution of wildlife species, their activity patterns and interactions among members of the …

Abstract Machine learning covers a large set of algorithms that can be trained to identify
patterns in data. Thanks to the increase in the amount of data and computing power …

We describe the development and application of a new convolutional neural network-based
photo-identification algorithm for individual humpback whales (Megaptera novaeangliae) …

Motivated by the need to estimate the abundance of marine mammal populations to inform
conservation assessments, especially relating to fishery bycatch, this paper provides …

Determining which species are at greatest risk, where they are most vulnerable, and what
are the trajectories of their communities and populations is critical for conservation and …

The flourishing application of drones within marine science provides more opportunity to
conduct photogrammetric studies on large and varied populations of many different species …

Wildlife camera traps and crowd-sourced image material provide novel possibilities to
monitor endangered animal species. The massive data volumes call for automatic methods …

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 …

The deep learning (DL) revolution is touching all scientific disciplines and corners of our
lives as a means of harnessing the power of big data. Marine ecology is no exception. New …