Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Semi-supervised Deep Learning for Image Classification with Distribution
  Mismatch: A Survey   Deep learning methodologies have been employed in several different fields,
with an outstanding success in image recognition applications, such as material
quality control, medical imaging, autonomous driving, etc. Deep learning models
rely on the abundance of labelled observations to train a prospective model.
These models are composed of millions of parameters to estimate, increasing the
need of more training observations. Frequently it is expensive to gather
labelled observations of data, making the usage of deep learning models not
ideal, as the model might over-fit data. In a semi-supervised setting,
unlabelled data is used to improve the levels of accuracy and generalization of
a model with small labelled datasets. Nevertheless, in many situations
different unlabelled data sources might be available. This raises the risk of a
significant distribution mismatch between the labelled and unlabelled datasets.
Such phenomena can cause a considerable performance hit to typical
semi-supervised deep learning frameworks, which often assume that both labelled
and unlabelled datasets are drawn from similar distributions. Therefore, in
this paper we study the latest approaches for semi-supervised deep learning for
image recognition. Emphasis is made in semi-supervised deep learning models
designed to deal with a distribution mismatch between the labelled and
unlabelled datasets. We address open challenges with the aim to encourage the
community to tackle them, and overcome the high data demand of traditional deep
learning pipelines under real-world usage settings.

20
The categories of this paper are: acc-phys
14
The categories of this paper are: math-ph
2
The categories of this paper are: math
10
The categories of this paper are: q-bio
25
The categories of this paper are: patt-sol
36
The categories of this paper are: cmp-lg
32
The categories of this paper are: atom-ph
22
The categories of this paper are: chao-dyn
13
The categories of this paper are: quant-ph
18
The categories of this paper are: econ
34
The categories of this paper are: chem-ph
8
The categories of this paper are: hep-ex
30
The categories of this paper are: q-alg
29
The categories of this paper are: funct-an
16
The categories of this paper are: stat
33
The categories of this paper are: plasm-ph