Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Live Target Detection with Deep Learning Neural Network and Unmanned
  Aerial Vehicle on Android Mobile Device   This paper describes the stages faced during the development of an Android
program which obtains and decodes live images from DJI Phantom 3 Professional
Drone and implements certain features of the TensorFlow Android Camera Demo
application. Test runs were made and outputs of the application were noted. A
lake was classified as seashore, breakwater and pier with the proximities of
24.44%, 21.16% and 12.96% respectfully. The joystick of the UAV controller and
laptop keyboard was classified with the proximities of 19.10% and 13.96%
respectfully. The laptop monitor was classified as screen, monitor and
television with the proximities of 18.77%, 14.76% and 14.00% respectfully. The
computer used during the development of this study was classified as notebook
and laptop with the proximities of 20.04% and 11.68% respectfully. A tractor
parked at a parking lot was classified with the proximity of 12.88%. A group of
cars in the same parking lot were classified as sports car, racer and
convertible with the proximities of 31.75%, 18.64% and 13.45% respectfully at
an inference time of 851ms.

36
The categories of this paper are: cmp-lg
23
The categories of this paper are: solv-int
28
The categories of this paper are: alg-geom
11
The categories of this paper are: hep-lat
26
The categories of this paper are: bayes-an
14
The categories of this paper are: math-ph
24
The categories of this paper are: dg-ga
4
The categories of this paper are: cond-mat
9
The categories of this paper are: nlin
27
The categories of this paper are: comp-gas
10
The categories of this paper are: q-bio
32
The categories of this paper are: atom-ph
15
The categories of this paper are: nucl-ex
13
The categories of this paper are: quant-ph
33
The categories of this paper are: plasm-ph
3
The categories of this paper are: physics