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MARLIT, an R Shiny Web App, Uses Deep Learning to Find Floating Marine Litter From Aerial Imagery
The MARLIT web app automatically locates and quantifies floating sea litter — and could assist with clean-up efforts.
Researchers at the Universitat de Barcelona, BIOST, and GRBIO in Spain have published a paper showing how a deep learning web application, written in R, could address the problem of large-scale marine litter. Meet MARLIT.
"Automatic aerial photography techniques combined with analytical algorithms are more efficient protocols for the control and study of [macro-litter in marine environments]", says first author Odei García-Garin of the study's focus. "However, automated remote sensing of these materials is at an early stage."

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