Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Adaptive Control of Embedding Strength in Image Watermarking using
  Neural Networks   Digital image watermarking has been widely used in different applications
such as copyright protection of digital media, such as audio, image, and video
files. Two opposing criteria of robustness and transparency are the goals of
watermarking methods. In this paper, we propose a framework for determining the
appropriate embedding strength factor. The framework can use most DWT and DCT
based blind watermarking approaches. We use Mask R-CNN on the COCO dataset to
find a good strength factor for each sub-block. Experiments show that this
method is robust against different attacks and has good transparency.

27
The categories of this paper are: comp-gas
7
The categories of this paper are: hep-th
32
The categories of this paper are: atom-ph
15
The categories of this paper are: nucl-ex
3
The categories of this paper are: physics
4
The categories of this paper are: cond-mat
28
The categories of this paper are: alg-geom
16
The categories of this paper are: stat
33
The categories of this paper are: plasm-ph
37
The categories of this paper are: supr-con
9
The categories of this paper are: nlin
13
The categories of this paper are: quant-ph
14
The categories of this paper are: math-ph
11
The categories of this paper are: hep-lat
31
The categories of this paper are: ao-sci
10
The categories of this paper are: q-bio