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Papers
20 resultsShowing papers similar to ImaMPs: Extensive image dataset of microplastics in freshwater from tourist areas in the State of Mexico, Mexico.
ClearImaMPs: Extensive image dataset of microplastics in freshwater from tourist areas in the State of Mexico, Mexico.
Researchers compiled an extensive image dataset of microplastics collected from freshwater bodies in tourist areas of the State of Mexico, providing a visual reference resource to support automated identification and classification of microplastic particles in Mexican aquatic ecosystems.
Spatiotemporal assessment of microplastic incidence in the Atoyac basin — a key watershed in Mexico
This spatiotemporal study quantified and characterized microplastics in freshwater and sediments across the Atoyac sub-basin in Mexico, documenting MP types, shapes, and sizes at sites impacted by urban, agricultural, and industrial activity over multiple sampling periods.
Morphological Detection and Classification of Microplastics and Nanoplastics Emerged from Consumer Products by Deep Learning
Researchers created a new open-source dataset of microscopy images for training AI models to automatically detect and classify micro- and nanoplastics. The dataset fills an important gap in available tools for microplastic research and provides a foundation for developing faster, more efficient methods to identify plastic contamination across environmental samples.
Deep Learning-Based Image Recognition System for Automated Microplastic Detection and Water Pollution Monitoring
This study developed a deep learning image recognition system to automate the detection and classification of microplastics from microscopy images of water samples. The system achieved high accuracy across particle types and sizes, offering a scalable and less labor-intensive alternative to manual microscopy for large-scale water pollution monitoring.
Identification of Microplastics in Aquatic Environments Using Oxidative Treatment and Automated Image Analysis
Researchers developed a cost-effective and replicable method for detecting microplastics in freshwater environments using oxidative treatment to digest organic matter from water samples, enabling cleaner isolation and more accurate identification of MP particles without requiring expensive instrumentation.
The state of microplastic pollution in México: a review and evolving perspectives
A PRISMA-based review of microplastic research in Mexico documented growing contamination across marine, freshwater, and terrestrial environments, characterized the dominant polymer types and particle shapes, and identified major knowledge gaps needing attention in the Mexican context.
A Machine Learning Approach To Microplastic Detection And Quantification In Aquatic Environments
This study developed a machine learning approach for detecting and quantifying microplastics in aquatic environments, demonstrating that automated image analysis can improve throughput and accuracy compared to manual microscopic counting for environmental monitoring applications.
First insight into microplastic groundwater pollution in Latin America: the case of a coastal aquifer in Northwest Mexico
Researchers conducted the first investigation of microplastic pollution in groundwater in Latin America, analyzing six capped boreholes in a coastal aquifer in northwest Mexico for microplastic abundance, concentration, and characteristics. The study detected microplastics in groundwater samples, establishing baseline contamination data for this understudied environmental compartment and raising concerns about drinking water quality in the region.
Microplastics in groundwater of two rural communities in Mexico
Researchers detected microplastics in drinking water from ten rural wells in two Mexican communities, finding diverse polymer types and morphologies at concentrations that suggest widespread groundwater MP contamination even in areas distant from major urban pollution sources.
Efficient Microplastic Detection in Water Using ResNet50 and Fluorescence Imaging
Researchers applied a ResNet50 deep learning model to fluorescence microscopy images of water samples, achieving high-accuracy classification of microplastics, demonstrating that deep learning can efficiently automate microplastic identification from microscopy data.
Deep Learning Approaches for Detection and Classification of Microplastics in Water for Clean Water Management
Researchers applied dual deep learning models (YOLOv8, YOLOv11, and several CNN architectures) to detect and classify microplastics in water, finding that these AI approaches could accurately identify plastic types across both aquatic and non-aquatic datasets.
Digital Image Analysis and Multivariate Data Analysis as Tools for the Identification of Microplastics in Surface Waters: The Case of the Vistula River (Central Europe)
Researchers demonstrated digital image analysis combined with microscopy as a tool for identifying and characterizing microplastic particles from Vistula River surface water samples, performing exhaustive quantitative and qualitative evaluation of 2D and 3D morphology to characterize MP abundance and composition.
Dataset of quantification and classification of microplastics in Mexican sandy beaches
This dataset presents the first national survey of microplastic contamination on 35 Mexican beaches across five coastal regions. Microplastics were found at all beaches, with fragments and pellets being the most common types, providing baseline data for monitoring plastic pollution along Mexico's coasts.
Automatic Counting and Classification of Microplastic Particles
Researchers developed an automatic system for counting and classifying microplastic particles in marine samples, applying image analysis techniques to address the growing problem of plastic debris entering the food chain via marine species ingestion.
Contaminación por microplásticos en el acuífero kárstico de la península de Yucatán
Researchers sampled water from cenotes and wells throughout the Yucatan karst aquifer and identified microplastic particles in every groundwater sample, with fibers comprising 94% of particles and concentrations ranging from 10 to 936 particles per liter, establishing that this primary regional drinking water source is universally contaminated with microplastics.
Detection of Microplastics Using Machine Learning
Researchers reviewed and demonstrated machine learning approaches for detecting and classifying microplastics in environmental samples, finding that automated image analysis and spectral classification methods can improve the speed and accuracy of microplastic monitoring compared to manual methods.
Microscopic Image Dataset with Segmentation and Detection Labels for Microplastic Analysis in Sewage: Enhancing Research and Environmental Monitoring
A labeled microscopic image dataset of microplastics in sewage was created with segmentation and detection annotations to support development and benchmarking of machine learning models for automated microplastic detection.
Microplastic analysis in urban areas and their impact on quality of life
Researchers reviewed the growing threat of microplastic pollution to biodiversity and human health, focusing on freshwater systems as a key exposure pathway. The study emphasizes the need for standardized identification methods for microplastics in freshwater environments.
Microscopic Image Dataset with Segmentation and Detection Labels for Microplastic Analysis in Sewage: Enhancing Research and Environmental Monitoring
Researchers created a novel microscopic image dataset with segmentation and detection labels specifically designed for identifying microplastics in sewage samples. The dataset is paired with deep learning models that can automatically detect and classify microplastic particles in complex wastewater images. This resource aims to accelerate environmental monitoring efforts by providing standardized training data for computer vision-based microplastic detection systems.
First insight into microplastic groundwater pollution in Latin America: the case of a coastal aquifer in Northwest Mexico
This is the first study to investigate microplastic contamination in groundwater in Latin America, examining a coastal aquifer in Northwest Mexico. Researchers found microplastics at all six sampled locations and at multiple depths, confirming that groundwater is not immune to this type of pollution. Since millions of people depend on groundwater for drinking water, these findings raise important questions about microplastic exposure through water supplies.