Energy Efficient Text Spotting Technique for Mobile Edge Computing

被引:2
作者
Jeong, Seonghwan [1 ]
Kwon, YoungMin [1 ]
机构
[1] State Univ New York, Comp Sci Dept, Incheon, South Korea
来源
2022 IEEE INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE CIRCUITS AND SYSTEMS (AICAS 2022): INTELLIGENT TECHNOLOGY IN THE POST-PANDEMIC ERA | 2022年
关键词
Edge computing; Mobile computing; Computational efficiency; Computer vision; Text spotting;
D O I
10.1109/AICAS54282.2022.9869940
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
We propose a new scene text spotting system which aims at minimizing the power consumption in mobile edge devices. We focused on preprocessing methods and changes in the processing pipeline. Overall, we removed non-text images from the processing pipeline to reduce power consumption and positioned texts at the center of the images to improve accuracy. Moreover, we were able to achieve a substantial power saving and increased text recognition accuracy. Compared to the baseline method, our proposed method shows an 80% higher performance score. The accuracy score was increased by 17% and the power consumption was reduced by 30% because we could reduce the execution count of the neural network by 40%.
引用
收藏
页码:106 / 109
页数:4
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