Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Deep Metric Learning for Few-Shot Image Classification: A Selective
  Review   Few-shot image classification is a challenging problem which aims to achieve
the human level of recognition based only on a small number of images. Deep
learning algorithms such as meta-learning, transfer learning, and metric
learning have been employed recently and achieved the state-of-the-art
performance. In this survey, we review representative deep metric learning
methods for few-shot classification, and categorize them into three groups
according to the major problems and novelties they focus on. We conclude this
review with a discussion on current challenges and future trends in few-shot
image classification.

3
The categories of this paper are: physics
16
The categories of this paper are: stat
30
The categories of this paper are: q-alg
31
The categories of this paper are: ao-sci
13
The categories of this paper are: quant-ph
18
The categories of this paper are: econ
25
The categories of this paper are: patt-sol
36
The categories of this paper are: cmp-lg
12
The categories of this paper are: nucl-th
24
The categories of this paper are: dg-ga
37
The categories of this paper are: supr-con
9
The categories of this paper are: nlin
4
The categories of this paper are: cond-mat
11
The categories of this paper are: hep-lat
23
The categories of this paper are: solv-int
0
The categories of this paper are: hep-ph