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MicroDetect-Net (MDN): Leveraging Deep Learning to Detect Microplastics in Clam Blood, a Step Towards Human Blood Analysis
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Researchers developed MicroDetect-Net, a deep learning model trained to detect microplastics in clam blood, demonstrating a pathway toward automated detection in human blood samples as plastic production exceeds 368 million tons annually and microplastics are found across all environmental and biological matrices.
With the prevalence of plastics exceeding over 368 million tons yearly, microplastic (MP) pollution has grown to an extent where air, water, soil, and living organisms have all been tested where microplastics have been detected. No less are these particles of...
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Advanced Microplastic Identification in Marine Environments via Hybrid Deep Learning
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Researchers propose a hybrid deep learning architecture combining 3D convolutional neural networks and Vision Transformers applied to hyperspectral imagery to detect and classify microplastics in turbid marine environments, capturing both local spectral signatures and global contextual patterns that single-model approaches miss.
Application of Artificial Intelligence to Improve Microplastic Identification
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This review examines how artificial intelligence -- including machine learning and computer vision approaches -- can improve the identification, classification, and measurement of microplastics during environmental sampling and analysis. AI-assisted identification addresses a major bottleneck in microplastic research by reducing the time and expertise required to process large sample volumes, enabling faster and more consistent data generation needed to assess human health exposure at scale.
FasterRes-FPN: A Deep Learning Approach for Microplastic Pollution Surveillance in Water Bodies
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Researchers developed FasterRes-FPN, a deep learning model for automated microplastic detection in water bodies, offering a faster and more cost-effective alternative to traditional microscopy and spectroscopy methods for large-scale aquatic pollution surveillance.
Detection of Microplastic in Seafood
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This review synthesizes research on the detection of microplastics in seafood, examining analytical methods and the prevalence of plastic contamination across commercially important marine species. Seafood is among the most direct dietary pathways for human microplastic ingestion, making reliable detection methods essential for quantifying health risks and informing food safety standards.
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When a large batch of papers lands in the Atlas, we read through it and send a short write-up of what stood out.