Edge computing at sea: high-throughput classification of in-situ plankton imagery for adaptive sampling

Edge computing at sea: high-throughput classification of in-situ plankton imagery for adaptive sampling

The small sizes of most marine plankton necessitate that plankton sampling occur on fine spatial scales, yet our questions often span large spatial areas. Underwater imaging can provide a solution to this sampling conundrum but collects large quantities of data that require an automated approach to...

Full description

Bibliographic Details
Main Authors: Moritz S. Schmid, Dominic Daprano, Malhar M. Damle, Christopher M. Sullivan, Su Sponaugle, Charles Cousin, Cedric Guigand, Robert K. Cowen
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-06-01
Series:Frontiers in Marine Science
Subjects:
adaptive sampling
edge computing
ocean technology
underwater imaging
plankton ecology
machine learning
Online Access:https://www.frontiersin.org/articles/10.3389/fmars.2023.1187771/full

Internet

https://www.frontiersin.org/articles/10.3389/fmars.2023.1187771/full

Similar Items