Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Reproduction of Lateral Inhibition-Inspired Convolutional Neural Network
  for Visual Attention and Saliency Detection   In recent years, neural networks have continued to flourish, achieving high
efficiency in detecting relevant objects in photos or simply recognizing
(classifying) these objects - mainly using CNN networks. Current solutions,
however, are far from ideal, because it often turns out that network can be
effectively confused with even natural images examples. I suspect that the
classification of an object is strongly influenced by the background pixels on
which the object is located. In my work, I analyze the above problem using for
this purpose saliency maps created by the LICNN network. They are designed to
suppress the neurons surrounding the examined object and, consequently, reduce
the contribution of background pixels to the classifier predictions. My
experiments on the natural and adversarial images datasets show that, indeed,
there is a visible correlation between the background and the wrong-classified
foreground object. This behavior of the network is not supported by human
experience, because, for example, we do not confuse the yellow school bus with
the snow plow just because it is on the snowy background.

34
The categories of this paper are: chem-ph
16
The categories of this paper are: stat
18
The categories of this paper are: econ
36
The categories of this paper are: cmp-lg
15
The categories of this paper are: nucl-ex
33
The categories of this paper are: plasm-ph
24
The categories of this paper are: dg-ga
7
The categories of this paper are: hep-th
22
The categories of this paper are: chao-dyn
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The categories of this paper are: eess
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The categories of this paper are: funct-an
2
The categories of this paper are: math
20
The categories of this paper are: acc-phys
26
The categories of this paper are: bayes-an
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The categories of this paper are: quant-ph
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The categories of this paper are: atom-ph