Union Regression Object Localization Based on Deep Reinforcement Learning

被引：0
作者：
Yao H.-G. [1 ]
Zhang W. [1 ]
Yang H.-Q. [1 ]
Yu J. [1 ]
机构：
[1] School of Computer Science and Engineering, Xi＇an Technological University, Xi＇an
来源：
Zidonghua Xuebao/Acta Automatica Sinica | 2023年 / 49卷 / 05期
关键词：
deep reinforcement learning; object localization; recurrent neural network (RNN); Visual attention mechanism;
D O I：
10.16383/j.aas.c200045
中图分类号：
学科分类号：
摘要：
To simulate the visual attention mechanism of the human eye, search and locate image objection quickly and efficiently, this paper proposes a union regression deep reinforcement learning object localization model based on recurrent neural network (RNN), which fuses the historical observation information with the observation information at the current time, then makes a comprehensive analysis to train the agent to quickly locate the object, and combine with the regressor to fine-tune the object bounding box positioned by the agent. Experiments show that the proposed model can accurately and rapidly locate the object in a few time steps. © 2023 Science Press. All rights reserved.
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页码：1089 / 1098
页数：9
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