Robustness Study of a Deep Convolutional Neural Network for Vehicle Detection in Aerial Imagery

被引：5
|
作者：
Ilina, O., V [1 ]
Tereshonok, M., V [1 ,2 ]
机构：
[1] Moscow Tech Univ Commun & Informat, Moscow 111024, Russia
[2] Natl Res Univ, Moscow Inst Phys & Technol, Dolgoprudnyi 141701, Moscow Oblast, Russia
来源：
JOURNAL OF COMMUNICATIONS TECHNOLOGY AND ELECTRONICS | 2022年 / 67卷 / 02期
基金：
俄罗斯科学基金会;
关键词：
This work was supported by the Russian Science Foundation; grant no. 18-72-10118;
D O I：
10.1134/S1064226922020048
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
The robustness of a deep convolutional neural network for vehicle detection in aerial imagery is analyzed. The study allows us to evaluate detection quality and correctness of a trained neural network. The method of improving noise immunity for an object detection system in aerial imagery is proposed.
引用
收藏
页码：164 / 170
页数：7
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