Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Optimal Approach for Image Recognition using Deep Convolutional
  Architecture   In the recent time deep learning has achieved huge popularity due to its
performance in various machine learning algorithms. Deep learning as
hierarchical or structured learning attempts to model high level abstractions
in data by using a group of processing layers. The foundation of deep learning
architectures is inspired by the understanding of information processing and
neural responses in human brain. The architectures are created by stacking
multiple linear or non-linear operations. The article mainly focuses on the
state-of-art deep learning models and various real world applications specific
training methods. Selecting optimal architecture for specific problem is a
challenging task, at a closing stage of the article we proposed optimal
approach to deep convolutional architecture for the application of image
recognition.

5
The categories of this paper are: gr-qc
28
The categories of this paper are: alg-geom
36
The categories of this paper are: cmp-lg
24
The categories of this paper are: dg-ga
14
The categories of this paper are: math-ph
26
The categories of this paper are: bayes-an
6
The categories of this paper are: astro-ph
15
The categories of this paper are: nucl-ex
10
The categories of this paper are: q-bio
0
The categories of this paper are: hep-ph
11
The categories of this paper are: hep-lat
17
The categories of this paper are: q-fin
18
The categories of this paper are: econ
27
The categories of this paper are: comp-gas
30
The categories of this paper are: q-alg
37
The categories of this paper are: supr-con