We can't find the internet
Attempting to reconnect
Something went wrong!
Hang in there while we get back on track
Plasmonic substrates enhanced micro-hyperspectral imaging for AI-based recognition of microplastics in water
No summary available — this paper's abstract is not included in the open metadata provided by the publisher. Learn why →
More Papers Like This
Remote Sensing Application for Monitoring Microplastic in Aquatic Environments
AI summary Read the abstract
Researchers reviewed how satellite imagery, UAVs, radar, and machine learning can detect and track micro- and macroplastics in rivers, lakes, and oceans far more efficiently than traditional nets and trawls. Better remote monitoring tools are essential for understanding where plastic pollution concentrates and how to prioritize cleanup efforts before it reaches the food chain.
Laser induced fluorescence and machine learning: a novel approach to microplastic identification
AI summary Read the abstract
Researchers combined laser-induced fluorescence with machine learning to identify microplastics in water in real time, achieving 97.6% accuracy in distinguishing plastics from other organic matter and 88.3% accuracy in identifying specific plastic types — a promising step toward automated ocean monitoring.
Research digests by email
When a large batch of papers lands in the Atlas, we read through it and send a short write-up of what stood out.