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Article
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AI-assigned paper type based on the abstract. Classification may not be perfect — flag errors using the feedback button.
Tier 2
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Original research — experimental, observational, or case-control study. Direct primary evidence.
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Automatic Detection of Microplastics by Deep Learning Enabled Digital Holography
Imaging and Applied Optics Congress
2020
12 citations
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Citation count from OpenAlex, updated daily. May differ slightly from the publisher's own count.
Yanmin Zhu,
Chok Hang Yeung,
Edmund Y. Lam
Summary
Researchers developed a digital holography system combined with deep learning to automatically detect and identify microplastics in water without manual image analysis. The system processes raw holographic images directly, offering a faster and more scalable approach to microplastic monitoring in environmental samples.
An inline digital holography with deep learning is developed to detect microplastics automatically from the raw holograms, without any additional image processing and analysis.