AIMC Topic: Plankton
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Deep learning meets marine biology: Optimized fused features and LIME-driven insights for automated plankton classification.
Computers in biology and medicine
Jun 1, 2025
Plankton are microorganisms that play an important role in marine food webs as primary producers in the trophic web. Traditional plankton identification methods using manual microscopy and sampling are time-consuming, labor-intensive, and prone to er...
EcoTransLearn: an R-package to easily use transfer learning for ecological studies-a plankton case study.
Bioinformatics (Oxford, England)
Dec 13, 2022
SUMMARY: In recent years, Deep Learning (DL) has been increasingly used in many fields, in particular in image recognition, due to its ability to solve problems where traditional machine learning algorithms fail. However, building an appropriate DL m...
The dynamic trophic architecture of open-ocean protist communities revealed through machine-guided metatranscriptomics.
Proceedings of the National Academy of Sciences of the United States of America
Feb 15, 2022
Intricate networks of single-celled eukaryotes (protists) dominate carbon flow in the ocean. Their growth, demise, and interactions with other microorganisms drive the fluxes of biogeochemical elements through marine ecosystems. Mixotrophic protists ...
A system of coordinated autonomous robots for Lagrangian studies of microbes in the oceanic deep chlorophyll maximum.
Science robotics
Jan 13, 2021
The deep chlorophyll maximum (DCM) layer is an ecologically important feature of the open ocean. The DCM cannot be observed using aerial or satellite remote sensing; thus, in situ observations are essential. Further, understanding the responses of mi...
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