Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Data Augmentation for Histopathological Images Based on
  Gaussian-Laplacian Pyramid Blending   Data imbalance is a major problem that affects several machine learning (ML)
algorithms. Such a problem is troublesome because most of the ML algorithms
attempt to optimize a loss function that does not take into account the data
imbalance. Accordingly, the ML algorithm simply generates a trivial model that
is biased toward predicting the most frequent class in the training data. In
the case of histopathologic images (HIs), both low-level and high-level data
augmentation (DA) techniques still present performance issues when applied in
the presence of inter-patient variability; whence the model tends to learn
color representations, which is related to the staining process. In this paper,
we propose a novel approach capable of not only augmenting HI dataset but also
distributing the inter-patient variability by means of image blending using the
Gaussian-Laplacian pyramid. The proposed approach consists of finding the
Gaussian pyramids of two images of different patients and finding the Laplacian
pyramids thereof. Afterwards, the left-half side and the right-half side of
different HIs are joined in each level of the Laplacian pyramid, and from the
joint pyramids, the original image is reconstructed. This composition combines
the stain variation of two patients, avoiding that color differences mislead
the learning process. Experimental results on the BreakHis dataset have shown
promising gains vis-a-vis the majority of DA techniques presented in the
literature.

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The categories of this paper are: dg-ga
37
The categories of this paper are: supr-con
4
The categories of this paper are: cond-mat
11
The categories of this paper are: hep-lat
9
The categories of this paper are: nlin
25
The categories of this paper are: patt-sol
13
The categories of this paper are: quant-ph
27
The categories of this paper are: comp-gas
26
The categories of this paper are: bayes-an
28
The categories of this paper are: alg-geom
35
The categories of this paper are: mtrl-th
15
The categories of this paper are: nucl-ex
34
The categories of this paper are: chem-ph
33
The categories of this paper are: plasm-ph
18
The categories of this paper are: econ
6
The categories of this paper are: astro-ph