Deep Learning for OCT Image-Based Methamphetamine Detection

This study explores the application of deep learning in forensic analysis by utilizing Optical Coherence Tomography (OCT) image classification to detect methamphetamine presence. The approach leverages convolutional neural networks (CNNs) to accurately identify drug-induced tissue alterations, offering a non-invasive and rapid tool for substance detection in forensic settings.

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