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Implementation of GPU Acceleration of Object Detection Application with Drone Video  

Park, Si-Hyun (Disciplinary Education, Sungkyunkwan University)
Park, Chun-Su (Computer Education, Sungkyunkwan University)
Publication Information
Journal of the Semiconductor & Display Technology / v.20, no.3, 2021 , pp. 117-119 More about this Journal
Abstract
With the development of the industry, the use of drones in specific mission flight is being actively studied. These drones fly a specified path and perform repetitive tasks. if the drone system will detect objects in real time, the performance of these mission flight will increase. In this paper, we implement object detection system and mount GPU acceleration to maximize the efficiency of limited device resources with drone video using Tensorflow Lite which enables in-device inference from a mobile device and Mobile SDK of DJI, a drone manufacture. For performance comparison, the average processing time per frame was measured when object detection was performed using only the CPU and when object detection was performed using the CPU and GPU at the same time.
Keywords
Drone; UAV; Object Detection; Deep-learning; GPU Acceleration;
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