Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: AuthNet: A Deep Learning based Authentication Mechanism using Temporal
  Facial Feature Movements   Biometric systems based on Machine learning and Deep learning are being
extensively used as authentication mechanisms in resource-constrained
environments like smartphones and other small computing devices. These
AI-powered facial recognition mechanisms have gained enormous popularity in
recent years due to their transparent, contact-less and non-invasive nature.
While they are effective to a large extent, there are ways to gain unauthorized
access using photographs, masks, glasses, etc. In this paper, we propose an
alternative authentication mechanism that uses both facial recognition and the
unique movements of that particular face while uttering a password, that is,
the temporal facial feature movements. The proposed model is not inhibited by
language barriers because a user can set a password in any language. When
evaluated on the standard MIRACL-VC1 dataset, the proposed model achieved an
accuracy of 98.1%, underscoring its effectiveness as an effective and robust
system. The proposed method is also data-efficient since the model gave good
results even when trained with only 10 positive video samples. The competence
of the training of the network is also demonstrated by benchmarking the
proposed system against various compounded Facial recognition and Lip reading
models.

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The categories of this paper are: comp-gas
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The categories of this paper are: solv-int
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The categories of this paper are: supr-con
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The categories of this paper are: math-ph
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The categories of this paper are: alg-geom
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The categories of this paper are: gr-qc
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The categories of this paper are: chem-ph
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The categories of this paper are: adap-org
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The categories of this paper are: q-fin
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The categories of this paper are: funct-an
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The categories of this paper are: hep-th
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The categories of this paper are: cond-mat
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The categories of this paper are: stat
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The categories of this paper are: math
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The categories of this paper are: mtrl-th
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The categories of this paper are: econ