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A Classification Framework for Concealed Weapon Detection Using Sub-Terahertz Images: LSTM-Based Optimized Deep Neural Network

Terahertz imaging technology is a promising method for preventing terrorist attacks due to its ability to penetrate various materials and reveal hidden objects without emitting harmful radiation. This study proposes a fast classification framework with high detection accuracy for terahertz imaging s...

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Hoofdauteurs: Ebru Efeoglu, Bahattin Turetken
Formaat: Artigo
Taal:Inglês
Gepubliceerd in: IEEE 2025-01-01
Reeks:IEEE Access
Onderwerpen:
Concealed weapon
image processing
LSTM
optimizers
terahertz imaging
Online toegang:https://ieeexplore.ieee.org/document/11258625/
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