Neural Network-Based Vehicle and Pedestrian Detection for Video Analysis System

被引：0
作者：
Babayan, Pavel V. [1 ]
Ershov, Maksim D. [1 ]
Erokhin, Denis Y. [1 ]
机构：
[1] RSREU, Dept Automat & Informat Technol Control, Ryazan, Russia
来源：
2019 8TH MEDITERRANEAN CONFERENCE ON EMBEDDED COMPUTING (MECO) | 2019年
关键词：
video analysis; image processing; object detection; pattern recognition; neural networks; machine learning;
D O I：
10.1109/meco.2019.8760125
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
In our research we compare various neural network architectures that are used for object detection and recognition. In this work vehicles and pedestrians are considered objects of interest. Modern artificial neural networks are able to detect and localize objects of known classes. This allows them to be used in various technical vision systems and video analysis systems. In this paper we compare three architectures (YOLO, Faster R-CNN, SSD) by the following criteria: processing speed, mAP, precision and recall.
引用
收藏
页码：310 / 314
页数：5
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