Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Salient Slices: Improved Neural Network Training and Performance with
  Image Entropy   As a training and analysis strategy for convolutional neural networks (CNNs),
we slice images into tiled segments and use, for training and prediction,
segments that both satisfy a criterion of information diversity and contain
sufficient content to support classification. In particular, we utilize image
entropy as the diversity criterion. This ensures that each tile carries as much
information diversity as the original image, and for many applications serves
as an indicator of usefulness in classification. To make predictions, a
probability aggregation framework is applied to probabilities assigned by the
CNN to the input image tiles. This technique facilitates the use of large,
high-resolution images that would be impractical to analyze unmodified;
provides data augmentation for training, which is particularly valuable when
image availability is limited; and the ensemble nature of the input for
prediction enhances its accuracy.

5
The categories of this paper are: gr-qc
14
The categories of this paper are: math-ph
3
The categories of this paper are: physics
27
The categories of this paper are: comp-gas
2
The categories of this paper are: math
23
The categories of this paper are: solv-int
37
The categories of this paper are: supr-con
36
The categories of this paper are: cmp-lg
32
The categories of this paper are: atom-ph
28
The categories of this paper are: alg-geom
6
The categories of this paper are: astro-ph
12
The categories of this paper are: nucl-th
26
The categories of this paper are: bayes-an
22
The categories of this paper are: chao-dyn
24
The categories of this paper are: dg-ga
18
The categories of this paper are: econ