Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: DoPAMINE: Double-sided Masked CNN for Pixel Adaptive Multiplicative
  Noise Despeckling   We propose DoPAMINE, a new neural network based multiplicative noise
despeckling algorithm. Our algorithm is inspired by Neural AIDE (N-AIDE), which
is a recently proposed neural adaptive image denoiser. While the original
N-AIDE was designed for the additive noise case, we show that the same
framework, i.e., adaptively learning a network for pixel-wise affine denoisers
by minimizing an unbiased estimate of MSE, can be applied to the multiplicative
noise case as well. Moreover, we derive a double-sided masked CNN architecture
which can control the variance of the activation values in each layer and
converge fast to high denoising performance during supervised training. In the
experimental results, we show our DoPAMINE possesses high adaptivity via
fine-tuning the network parameters based on the given noisy image and achieves
significantly better despeckling results compared to SAR-DRN, a
state-of-the-art CNN-based algorithm.

26
The categories of this paper are: bayes-an
17
The categories of this paper are: q-fin
11
The categories of this paper are: hep-lat
25
The categories of this paper are: patt-sol
21
The categories of this paper are: adap-org
16
The categories of this paper are: stat
6
The categories of this paper are: astro-ph
36
The categories of this paper are: cmp-lg
18
The categories of this paper are: econ
5
The categories of this paper are: gr-qc
28
The categories of this paper are: alg-geom
33
The categories of this paper are: plasm-ph
2
The categories of this paper are: math
30
The categories of this paper are: q-alg
27
The categories of this paper are: comp-gas
12
The categories of this paper are: nucl-th