Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Personal Identification Using Ultrawideband Radar Measurement of Walking
  and Sitting Motions and a Convolutional Neural Network   This study proposes a personal identification technique that applies machine
learning with a two-layered convolutional neural network to spectrogram images
obtained from radar echoes of a target person in motion. The walking and
sitting motions of six participants were measured using an ultrawideband radar
system. Time-frequency analysis was applied to the radar signal to generate
spectrogram images containing the micro-Doppler components associated with limb
movements. A convolutional neural network was trained using the spectrogram
images with personal labels to achieve radar-based personal identification. The
personal identification accuracies were evaluated experimentally to demonstrate
the effectiveness of the proposed technique.

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The categories of this paper are: mtrl-th
23
The categories of this paper are: solv-int
33
The categories of this paper are: plasm-ph
7
The categories of this paper are: hep-th
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The categories of this paper are: quant-ph
1
The categories of this paper are: cs
3
The categories of this paper are: physics
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The categories of this paper are: chem-ph
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The categories of this paper are: bayes-an
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The categories of this paper are: dg-ga
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The categories of this paper are: patt-sol
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The categories of this paper are: q-fin
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The categories of this paper are: chao-dyn
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The categories of this paper are: hep-ex
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The categories of this paper are: astro-ph
10
The categories of this paper are: q-bio