Computer Vision Pipeline for Automated Antarctic Krill Analysis

Avatar
Poster
Voice is AI-generated
Connected to paperThis paper is a preprint and has not been certified by peer review

Computer Vision Pipeline for Automated Antarctic Krill Analysis

Authors

Mazvydas Gudelis, Michal Mackiewicz, Julie Bremner, Sophie Fielding

Abstract

British Antarctic Survey (BAS) researchers launch annual expeditions to the Antarctic in order to estimate Antarctic Krill biomass and assess the change from previous years. These comparisons provide insight into the effects of the current environment on this key component of the marine food chain. In this work we have developed tools for automating the data collection and analysis process, using web-based image annotation tools and deep learning image classification and regression models. We achieve highly accurate krill instance segmentation results with an average 77.28% AP score, as well as separate maturity stage and length estimation of krill specimens with 62.99% accuracy and a 1.96 mm length error respectively.

Follow Us on

0 comments

Add comment