Abstract:This paper explores the use of deep learning
architectures to identify and categorize infrared spectral data with
the objective of classifying drugs and toxins with a high level of
accuracy. The model proposed uses a custom convolutional
neural network to learn the spectrum of 192 drugs and 207 toxins.
Variations in the architecture and number of blocks were iterated
to find the best possible fit. A real-time implementation of such a
model faces a lot of issues such as noise from different sources,
spectral ma… Show more
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