AIMC Topic: Plastics

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A machine learning algorithm for high throughput identification of FTIR spectra: Application on microplastics collected in the Mediterranean Sea.

Chemosphere
The development of methods to automatically determine the chemical nature of microplastics by FTIR-ATR spectra is an important challenge. A machine learning method, named k-nearest neighbors classification, has been applied on spectra of microplastic...

Identifying floating plastic marine debris using a deep learning approach.

Environmental science and pollution research international
Estimating the volume of macro-plastics which dot the world's oceans is one of the most pressing environmental concerns of our time. Prevailing methods for determining the amount of floating plastic debris, usually conducted manually, are time demand...

Marine litter accumulation along the Bulgarian Black Sea coast: Categories and predominance.

Waste management (New York, N.Y.)
Quantitative assessment of marine litter (ML) along the Bulgarian Black Sea coastline was presented. ML surveys were conducted every season in a total of 8 beach monitoring sites during 2015-2016. Eight main categories of material were determined, ba...

Microplastics do not increase toxicity of a hydrophobic organic chemical to marine plankton.

Marine pollution bulletin
Planktonic sea-urchin larvae actively ingest polyethylene microplastics (MP) that accumulate in the larval stomach and can be distinguished from natural food using polarized light microscopy. MP filtering rates were similar to those of natural partic...

Use of a convolutional neural network for the classification of microbeads in urban wastewater.

Chemosphere
Scientists are on the lookout for a practical model that can serve as a standard for sorting out, identifying, and characterizing microplastics which are common occurrences in water sources and wastewaters. The microbeads (MBs) used in cosmetics and ...

Plastics detection and sorting using hyperspectral sensing and machine learning algorithms.

Waste management (New York, N.Y.)
Plastic waste second life management requires effective detection (and sorting if necessary) techniques to tackle the environmental challenge it poses. This research explores the application of hyperspectral imaging in the spectral range 900-1700 nm ...

A lightweight spatial and spectral CNN model for classifying floating marine plastic debris using hyperspectral images.

Marine pollution bulletin
Marine plastic debris poses a significant environmental threat. In order to study and combat this pollution, efficient and automated detection methods are essential. Hyperspectral imaging and deep learning provide a robust framework for classifying f...

Machine Learning Advancements and Strategies in Microplastic and Nanoplastic Detection.

Environmental science & technology
Microplastics (MPs) and nanoplastics (NPs) present formidable global environmental challenges with serious risks to human health and ecosystem sustainability. Despite their significance, the accurate assessment of environmental MP and NP pollution re...

Assessment of virtual bracket removal by artificial intelligence and thermoplastic retainer fit.

American journal of orthodontics and dentofacial orthopedics : official publication of the American Association of Orthodontists, its constituent societies, and the American Board of Orthodontics
INTRODUCTION: Digital orthodontics is here to make our specialty more efficient, and the integration of artificial intelligence (AI) is no exception. This study aimed to compare the accuracy of a workflow involving virtual bracket removal (VBR) by AI...