Detection and imaging of chemicals and hidden explosives using terahertz time-domain spectroscopy and deep learning
Peer-Reviewed Publication
Updates every hour. Last Updated: 10-May-2026 17:16 ET (10-May-2026 21:16 GMT/UTC)
While terahertz spectroscopy offers a promising solution for non-invasive chemical detection, conventional methods often struggle in real-world environments where sample geometry and packaging distort the signal. UCLA researchers addressed this by creating a robust chemical imaging system that integrates high-performance terahertz time-domain spectroscopy with deep learning neural networks. By analyzing individual time-domain pulses rather than terahertz spectra, this system effectively identifies explosives with pixel-level precision, achieving high classification accuracy even for targets concealed behind opaque coverings.
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