Annotating very high-resolution satellite imagery: A whale case study.

The use of very high-resolution (VHR) optical satellites is gaining momentum in the field of wildlife monitoring, particularly for whales, as this technology is showing potential for monitoring the less studied regions. However, surveying large areas using VHR optical satellite imagery requires the development of automated systems to detect targets. Machine learning approaches require large training datasets of annotated images.

Applying deep learning to right whale photo identification.

Photo identification is an important tool for estimating abundance and monitoring population trends over time. However, manually matching photographs to known individuals is time-consuming. Motivated by recent developments in image recognition, we hosted a data science challenge on the crowdsourcing platform Kaggle to automate the identification of endangered North Atlantic right whales (Eubalaena glacialis).

Habitat-based cetacean density models for the U.S. Atlantic and Gulf of Mexico.

Cetaceans are protected worldwide but vulnerable to incidental harm from an expanding array of human activities at sea. Managing potential hazards to these highly-mobile populations increasingly requires a detailed understanding of their seasonal distributions and habitats. Pursuant to the urgent need for this knowledge for the U.

Vocal development in captive harbor seal pups, Phoca vitulina richardii: age, sex, and individual differences.

The goal of this research was to determine when harbor seal pup vocalizations become sufficiently distinctive to allow individual recognition. A total of 4593 calls were analyzed from 15 captive pups. Nineteen were harsh, broadband, staccato calls used in an aggressive context.