[HTML][HTML] Optical sensors and machine learning algorithms in sensor-based material flow characterization for mechanical recycling processes: A systematic literature …
Digital technologies hold enormous potential for improving the performance of future-
generation sorting and processing plants; however, this potential remains largely untapped …
generation sorting and processing plants; however, this potential remains largely untapped …
Recyclable waste image recognition based on deep learning
This study aims to improve the accuracy of waste sorting through deep learning and to
provide a possibility for intelligent waste classification based on computer vision/mobile …
provide a possibility for intelligent waste classification based on computer vision/mobile …
Microplastics as vectors of other contaminants: Analytical determination techniques and remediation methods
MV Zambrano-Pinto, R Tinizaray-Castillo… - Science of The Total …, 2024 - Elsevier
The ubiquitous and persistent presence of microplastics (MPs) in aquatic and terrestrial
ecosystems has raised global concerns due to their detrimental effects on human health and …
ecosystems has raised global concerns due to their detrimental effects on human health and …
An insight on sampling, identification, quantification and characteristics of microplastics in solid wastes
Microplastics (MPs) have attracted wide attention all over the world as a remarkable
pollutant. While MPs are spreading throughout several complex environmental matrices …
pollutant. While MPs are spreading throughout several complex environmental matrices …
A machine learning based classification models for plastic recycling using different wavelength range spectrums
Currently, the use and production of plastic are on the rising trend, leading to the increase in
waste generation and consumption of raw materials, making it one of the most significant …
waste generation and consumption of raw materials, making it one of the most significant …
[HTML][HTML] Plastic classification via in-line hyperspectral camera analysis and unsupervised machine learning
An increase in the quality of recycled plastic is paramount to address the global plastic
challenge and applicability of recycled plastics. A potent approach is mechanical plastic …
challenge and applicability of recycled plastics. A potent approach is mechanical plastic …
Advancing floating macroplastic detection from space using experimental hyperspectral imagery
Airborne and spaceborne remote sensing (RS) collecting hyperspectral imagery provides
unprecedented opportunities for the detection and monitoring of floating riverine and marine …
unprecedented opportunities for the detection and monitoring of floating riverine and marine …
[HTML][HTML] Prediction of polyethylene density from FTIR and Raman spectroscopy using multivariate data analysis
To contribute to the targeted 10 million tons per year of recycled plastic in Europe by 2025
and to improve the mechanical sorting degree of polyethylene (PE) products, density …
and to improve the mechanical sorting degree of polyethylene (PE) products, density …
[HTML][HTML] An ensemble machine learning method for microplastics identification with FTIR spectrum
Abstract Microplastics (MPs)(size< 5 mm) marine pollution have been investigated and
monitored by many researchers and found in many coasts around the world. These toxic …
monitored by many researchers and found in many coasts around the world. These toxic …
Classification and distribution of freshwater microplastics along the Italian Po river by hyperspectral imaging
L Fiore, S Serranti, C Mazziotti, E Riccardi… - … Science and Pollution …, 2022 - Springer
In this work, freshwater microplastic samples collected from four different stations along the
Italian Po river were characterized in terms of abundance, distribution, category …
Italian Po river were characterized in terms of abundance, distribution, category …