Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Train and Deploy an Image Classifier for Disaster Response   With Deep Learning Image Classification becoming more powerful each year, it
is apparent that its introduction to disaster response will increase the
efficiency that responders can work with. Using several Neural Network Models,
including AlexNet, ResNet, MobileNet, DenseNets, and 4-Layer CNN, we have
classified flood disaster images from a large image data set with up to 79%
accuracy. Our models and tutorials for working with the data set have created a
foundation for others to classify other types of disasters contained in the
images.

29
The categories of this paper are: funct-an
19
The categories of this paper are: eess
10
The categories of this paper are: q-bio
35
The categories of this paper are: mtrl-th
14
The categories of this paper are: math-ph
0
The categories of this paper are: hep-ph
3
The categories of this paper are: physics
26
The categories of this paper are: bayes-an
15
The categories of this paper are: nucl-ex
16
The categories of this paper are: stat
17
The categories of this paper are: q-fin
18
The categories of this paper are: econ
22
The categories of this paper are: chao-dyn
4
The categories of this paper are: cond-mat
5
The categories of this paper are: gr-qc
9
The categories of this paper are: nlin