Using Deep Networks for Drone Detection

被引:125
作者
Aker, Cemal [1 ]
Kalkan, Sinan [1 ]
机构
[1] Middle East Tech Univ, KOVAN Res Lab Comp Engn, Ankara, Turkey
来源
2017 14TH IEEE INTERNATIONAL CONFERENCE ON ADVANCED VIDEO AND SIGNAL BASED SURVEILLANCE (AVSS) | 2017年
关键词
D O I
10.1109/avss.2017.8078539
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Drone detection is the problem of finding the smallest rectangle that encloses the drone(s) in a video sequence. In this study, we propose a solution using an end-to-end object detection model based on convolutional neural networks. To solve the scarce data problem for training the network, we propose an algorithm for creating an extensive artificial dataset by combining background-subtracted real images. With this approach, we can achieve precision and recall values both of which are high at the same time.
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页数:6
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