Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Camera-based Image Forgery Localization using Convolutional Neural
  Networks   Camera fingerprints are precious tools for a number of image forensics tasks.
A well-known example is the photo response non-uniformity (PRNU) noise pattern,
a powerful device fingerprint. Here, to address the image forgery localization
problem, we rely on noiseprint, a recently proposed CNN-based camera model
fingerprint. The CNN is trained to minimize the distance between same-model
patches, and maximize the distance otherwise. As a result, the noiseprint
accounts for model-related artifacts just like the PRNU accounts for
device-related non-uniformities. However, unlike the PRNU, it is only mildly
affected by residuals of high-level scene content. The experiments show that
the proposed noiseprint-based forgery localization method improves over the
PRNU-based reference.

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The categories of this paper are: dg-ga
9
The categories of this paper are: nlin
26
The categories of this paper are: bayes-an
6
The categories of this paper are: astro-ph
36
The categories of this paper are: cmp-lg
13
The categories of this paper are: quant-ph
35
The categories of this paper are: mtrl-th
37
The categories of this paper are: supr-con
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The categories of this paper are: patt-sol
8
The categories of this paper are: hep-ex
31
The categories of this paper are: ao-sci
20
The categories of this paper are: acc-phys
18
The categories of this paper are: econ
22
The categories of this paper are: chao-dyn
16
The categories of this paper are: stat
21
The categories of this paper are: adap-org