Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Does deep learning always outperform simple linear regression in optical
  imaging?   Deep learning has been extensively applied in many optical imaging
applications in recent years. Despite the success, the limitations and
drawbacks of deep learning in optical imaging have been seldom investigated. In
this work, we show that conventional linear-regression-based methods can
outperform the previously proposed deep learning approaches for two black-box
optical imaging problems in some extent. Deep learning demonstrates its
weakness especially when the number of training samples is small. The
advantages and disadvantages of linear-regression-based methods and deep
learning are analyzed and compared. Since many optical systems are essentially
linear, a deep learning network containing many nonlinearity functions
sometimes may not be the most suitable option.

24
The categories of this paper are: dg-ga
29
The categories of this paper are: funct-an
23
The categories of this paper are: solv-int
2
The categories of this paper are: math
27
The categories of this paper are: comp-gas
35
The categories of this paper are: mtrl-th
28
The categories of this paper are: alg-geom
3
The categories of this paper are: physics
17
The categories of this paper are: q-fin
0
The categories of this paper are: hep-ph
31
The categories of this paper are: ao-sci
32
The categories of this paper are: atom-ph
34
The categories of this paper are: chem-ph
6
The categories of this paper are: astro-ph
14
The categories of this paper are: math-ph
30
The categories of this paper are: q-alg