Stamatia Galata, Ian Walkington, Timothy Lane, Konstadinos Kiriakoulakis, Jonathan Dick
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Rapid Detection of Microfibres in Environmental Samples Using Open-Source Visual Recognition Models
Microplastics, particularly microfibres (< 5 mm), are a significant environmental pollutant. Detecting and quantifying them in complex matrices is challenging and time-consuming. This study presents two open-source visual recognition models, YOLOv7 and Mask R-CNN, trained on extensive datasets for efficient microfibre identification in environmental samples. The YOLOv7 model is a new introduction to the microplastic quantification research, while Mask R-CNN has been previously used in similar studies. YOLOv7, with 71.4% accuracy, and Mask R-CNN, with 49.9% accuracy, demonstrate effective detection capabilities. Tested on aquatic samples from Seyðisfjörður, Iceland, YOLOv7 rapidly identifies microfibres, outperforming manual methods in speed. These models are user-friendly and widely accessible, making them valuable tools for microplastic contamination assessment. Their rapid processing offers results in seconds, enhancing research efficiency in microplastic pollution studies. By providing these models openly, we aim to support and advance microplastic quantification research. The integration of these advanced technologies with environmental science represents a significant step forward in addressing the global issue of microplastic pollution and its ecological and health impacts.
期刊介绍:
The Journal of Hazardous Materials serves as a global platform for promoting cutting-edge research in the field of Environmental Science and Engineering. Our publication features a wide range of articles, including full-length research papers, review articles, and perspectives, with the aim of enhancing our understanding of the dangers and risks associated with various materials concerning public health and the environment. It is important to note that the term "environmental contaminants" refers specifically to substances that pose hazardous effects through contamination, while excluding those that do not have such impacts on the environment or human health. Moreover, we emphasize the distinction between wastes and hazardous materials in order to provide further clarity on the scope of the journal. We have a keen interest in exploring specific compounds and microbial agents that have adverse effects on the environment.