Document of bibliographic reference 355903

BibliographicReference record

Type
Bibliographic resource
Type of document
Journal article
BibLvlCode
AS
Title
FathomNet: A global image database for enabling artificial intelligence in the ocean
Abstract
The ocean is experiencing unprecedented rapid change, and visually monitoring marine biota at the spatiotemporal scales needed for responsible stewardship is a formidable task. As baselines are sought by the research community, the volume and rate of this required data collection rapidly outpaces our abilities to process and analyze them. Recent advances in machine learning enables fast, sophisticated analysis of visual data, but have had limited success in the ocean due to lack of data standardization, insufficient formatting, and demand for large, labeled datasets. To address this need, we built FathomNet, an open-source image database that standardizes and aggregates expertly curated labeled data. FathomNet has been seeded with existing iconic and non-iconic imagery of marine animals, underwater equipment, debris, and other concepts, and allows for future contributions from distributed data sources. We demonstrate how FathomNet data can be used to train and deploy models on other institutional video to reduce annotation effort, and enable automated tracking of underwater concepts when integrated with robotic vehicles. As FathomNet continues to grow and incorporate more labeled data from the community, we can accelerate the processing of visual data to achieve a healthy and sustainable global ocean.
WebOfScience code
https://www.webofscience.com/wos/woscc/full-record/WOS:001012301900001
Bibliographic citation
Katija, K.; Orenstein, E.; Schlining, B.; Lundsten, L.; Barnard, K.; Sainz, G.; Boulais, O.; Cromwell, M.; Butler, E.; Woodward, B.; Bell, K.L.C. (2022). FathomNet: A global image database for enabling artificial intelligence in the ocean. NPG Scientific Reports 12(1): 15914. https://dx.doi.org/10.1038/s41598-022-19939-2
Topic
Marine
Is peer reviewed
true
Access rights
open access
Is accessible for free
true

Authors

author
Name
Kakani Katija
author
Name
Eric Orenstein
author
Name
Brian Schlining
author
Name
Lonny Lundsten
author
Name
Kevin Barnard
author
Name
Giovanna Sainz
author
Name
Oceane Boulais
author
Name
Megan Cromwell
author
Name
Erin Butler
author
Name
Benjamin Woodward
author
Name
Katherine Bell

Links

referenced creativework
type
DOI
accessURL
https://dx.doi.org/10.1038/s41598-022-19939-2

Document metadata

date created
2022-10-03
date modified
2022-11-08