Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Precipitaion Nowcasting using Deep Neural Network   Precipitation nowcasting is of great importance for weather forecast users,
for activities ranging from outdoor activities and sports competitions to
airport traffic management. In contrast to long-term precipitation forecasts
which are traditionally obtained from numerical models, precipitation
nowcasting needs to be very fast. It is therefore more challenging to obtain
because of this time constraint. Recently, many machine learning based methods
had been proposed. We propose the use three popular deep learning models
(U-net, ConvLSTM and SVG-LP) trained on two-dimensional precipitation maps for
precipitation nowcasting. We proposed an algorithm for patch extraction to
obtain high resolution precipitation maps. We proposed a loss function to solve
the blurry image issue and to reduce the influence of zero value pixels in
precipitation maps.

33
The categories of this paper are: plasm-ph
10
The categories of this paper are: q-bio
27
The categories of this paper are: comp-gas
0
The categories of this paper are: hep-ph
16
The categories of this paper are: stat
24
The categories of this paper are: dg-ga
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The categories of this paper are: funct-an
28
The categories of this paper are: alg-geom
15
The categories of this paper are: nucl-ex
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The categories of this paper are: ao-sci
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The categories of this paper are: mtrl-th
34
The categories of this paper are: chem-ph
18
The categories of this paper are: econ
26
The categories of this paper are: bayes-an
23
The categories of this paper are: solv-int
25
The categories of this paper are: patt-sol