Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Deep Learning for automatic sale receipt understanding   As a general rule, data analytics are now mandatory for companies. Scanned
document analysis brings additional challenges introduced by paper damages and
scanning quality.In an industrial context, this work focuses on the automatic
understanding of sale receipts which enable access to essential and accurate
consumption statistics. Given an image acquired with a smart-phone, the
proposed work mainly focuses on the first steps of the full tool chain which
aims at providing essential information such as the store brand, purchased
products and related prices with the highest possible confidence. To get this
high confidence level, even if scanning is not perfectly controlled, we propose
a double check processing tool-chain using Deep Convolutional Neural Networks
(DCNNs) on one hand and more classical image and text processings on another
hand.The originality of this work relates in this double check processing and
in the joint use of DCNNs for different applications and text analysis.

9
The categories of this paper are: nlin
2
The categories of this paper are: math
0
The categories of this paper are: hep-ph
32
The categories of this paper are: atom-ph
3
The categories of this paper are: physics
8
The categories of this paper are: hep-ex
13
The categories of this paper are: quant-ph
27
The categories of this paper are: comp-gas
17
The categories of this paper are: q-fin
34
The categories of this paper are: chem-ph
37
The categories of this paper are: supr-con
5
The categories of this paper are: gr-qc
25
The categories of this paper are: patt-sol
12
The categories of this paper are: nucl-th
16
The categories of this paper are: stat
23
The categories of this paper are: solv-int