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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 accuracies of 24.44%, 21.16% and
12.96% respectfully. The joystick of the UAV controller and
laptop keyboard was classified with the accuracies of 19.10% and
13.96% respectfully. The laptop monitor was classified as screen,
monitor and television with the accuracies 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
accuracies of 20.04% and 11.68% respectfully. A tractor parked
at a parking lot was classified with the accuracy of 12.88%. A
group of cars in the same parking lot were classified as sports car,
racer and convertible with the accuracies of 31.75%, 18.64% and
13.45% respectfully at an inference time of 851ms.
International Conference on Advanced Technologies, Computer Engineering and Science
ICATCES
Ali Canberk Anar
Erkan Bostanci
Mehmet Serdar Guzel