Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Neural Networks for Fashion Image Classification and Visual Search   We discuss two potentially challenging problems faced by the ecommerce
industry. One relates to the problem faced by sellers while uploading pictures
of products on the platform for sale and the consequent manual tagging
involved. It gives rise to misclassifications leading to its absence from
search results. The other problem concerns with the potential bottleneck in
placing orders when a customer may not know the right keywords but has a visual
impression of an image. An image based search algorithm can unleash the true
potential of ecommerce by enabling customers to click a picture of an object
and search for similar products without the need for typing. In this paper, we
explore machine learning algorithms which can help us solve both these
problems.

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The categories of this paper are: hep-th
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The categories of this paper are: atom-ph
21
The categories of this paper are: adap-org
15
The categories of this paper are: nucl-ex
31
The categories of this paper are: ao-sci
20
The categories of this paper are: acc-phys
16
The categories of this paper are: stat
5
The categories of this paper are: gr-qc
10
The categories of this paper are: q-bio
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The categories of this paper are: chem-ph
30
The categories of this paper are: q-alg
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The categories of this paper are: bayes-an
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The categories of this paper are: q-fin
36
The categories of this paper are: cmp-lg
11
The categories of this paper are: hep-lat
6
The categories of this paper are: astro-ph