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Computer Science > Computer Vision and Pattern Recognition

Title: Live Target Detection with Deep Learning Neural Network and Unmanned Aerial Vehicle on Android Mobile Device

Abstract: 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.
Comments: 5 pages
Subjects: Computer Vision and Pattern Recognition (cs.CV)
Cite as: arXiv:1803.07015 [cs.CV]
  (or arXiv:1803.07015v1 [cs.CV] for this version)

Submission history

From: Erkan Bostanci [view email]
[v1] Mon, 19 Mar 2018 16:15:22 GMT (1463kb)