Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Automatic Detection and Classification of Symbols in Engineering
  Drawings   A method of finding and classifying various components and objects in a
design diagram, drawing, or planning layout is proposed. The method
automatically finds the objects present in a legend table and finds their
position, count and related information with the help of multiple deep neural
networks. The method is pre-trained on several drawings or design templates to
learn the feature set that may help in representing the new templates. For a
template not seen before, it does not require any training with template
dataset. The proposed method may be useful in multiple industry applications
such as design validation, object count, connectivity of components, etc. The
method is generic and domain independent.

34
The categories of this paper are: chem-ph
6
The categories of this paper are: astro-ph
4
The categories of this paper are: cond-mat
8
The categories of this paper are: hep-ex
21
The categories of this paper are: adap-org
27
The categories of this paper are: comp-gas
18
The categories of this paper are: econ
23
The categories of this paper are: solv-int
11
The categories of this paper are: hep-lat
26
The categories of this paper are: bayes-an
9
The categories of this paper are: nlin
2
The categories of this paper are: math
5
The categories of this paper are: gr-qc
19
The categories of this paper are: eess
32
The categories of this paper are: atom-ph
3
The categories of this paper are: physics