Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Domain Adaptation for Ear Recognition Using Deep Convolutional Neural
  Networks   In this paper, we have extensively investigated the unconstrained ear
recognition problem. We have first shown the importance of domain adaptation,
when deep convolutional neural network models are used for ear recognition. To
enable domain adaptation, we have collected a new ear dataset using the
Multi-PIE face dataset, which we named as Multi-PIE ear dataset. To improve the
performance further, we have combined different deep convolutional neural
network models. We have analyzed in depth the effect of ear image quality, for
example illumination and aspect ratio, on the classification performance.
Finally, we have addressed the problem of dataset bias in the ear recognition
field. Experiments on the UERC dataset have shown that domain adaptation leads
to a significant performance improvement. For example, when VGG-16 model is
used and the domain adaptation is applied, an absolute increase of around 10\%
has been achieved. Combining different deep convolutional neural network models
has further improved the accuracy by 4\%. It has also been observed that image
quality has an influence on the results. In the experiments that we have
conducted to examine the dataset bias, given an ear image, we were able to
classify the dataset that it has come from with 99.71\% accuracy, which
indicates a strong bias among the ear recognition datasets.

34
The categories of this paper are: chem-ph
24
The categories of this paper are: dg-ga
5
The categories of this paper are: gr-qc
17
The categories of this paper are: q-fin
31
The categories of this paper are: ao-sci
8
The categories of this paper are: hep-ex
18
The categories of this paper are: econ
37
The categories of this paper are: supr-con
7
The categories of this paper are: hep-th
19
The categories of this paper are: eess
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The categories of this paper are: acc-phys
23
The categories of this paper are: solv-int
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The categories of this paper are: patt-sol
2
The categories of this paper are: math
4
The categories of this paper are: cond-mat
16
The categories of this paper are: stat