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
相关论文
共 50 条
  • [41] Optimizing Energy Efficient Cloud Architectures for Edge Computing: A Comprehensive Review
    Gamage, Ta
    Perera, Indika
    INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, 2024, 15 (11) : 637 - 645
  • [42] High Speed and Energy Efficient Deep Neural Network for Edge Computing
    Bai, Kangjun
    Liu, Shiya
    Yi, Yang
    SEC'19: PROCEEDINGS OF THE 4TH ACM/IEEE SYMPOSIUM ON EDGE COMPUTING, 2019, : 347 - 349
  • [43] DAG Scheduling in Mobile Edge Computing
    Li, Guopeng
    Tan, Haisheng
    Liu, Liuyan
    Zhou, Hao
    Jiang, Shaofeng H-C
    Han, Zhenhua
    Li, Xiang-Yang
    Chen, Guoliang
    ACM TRANSACTIONS ON SENSOR NETWORKS, 2024, 20 (01)
  • [44] Fair Energy Efficiency Scheduling in NOMA-Based Mobile Edge Computing
    Hu Han
    Bao Nan
    Ling Zhang
    Shen Le
    JOURNAL OF ELECTRONICS & INFORMATION TECHNOLOGY, 2021, 43 (12) : 3563 - 3570
  • [45] Energy Minimization of Mobile Edge Computing Networks With HARQ in the Finite Blocklength Regime
    Zhu, Yao
    Hu, Yulin
    Schmeink, Anke
    Gross, James
    IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, 2022, 21 (09) : 7105 - 7120
  • [46] Energy-Efficient Offloading Based on Efficient Cognitive Energy Management Scheme in Edge Computing Device with Energy Optimization
    Kaliappan, Vishnu Kumar
    Ranganathan, Aravind Babu Lalpet
    Periasamy, Selvaraju
    Thirumalai, Padmapriya
    Tuan Anh Nguyen
    Jeon, Sangwoo
    Min, Dugki
    Choi, Enumi
    ENERGIES, 2022, 15 (21)
  • [47] Selective Edge Computing for Mobile Analytics
    Galanopoulos, Apostolos
    Iosifidis, George
    Salonidis, Theodoros
    Leith, Douglas J.
    IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT, 2022, 19 (03): : 3090 - 3104
  • [48] Energy-efficient Edge Server Management for Edge Computing: A Game-theoretical Approach
    Cui, Guangming
    He, Qiang
    Xia, Xiaoyu
    Chen, Feifei
    Yang, Yun
    51ST INTERNATIONAL CONFERENCE ON PARALLEL PROCESSING, ICPP 2022, 2022,
  • [49] Artificial intelligence aware and security-enhanced traceback technique in mobile edge computing
    Liu, Yuxin
    Wang, Tian
    Zhang, Shaobo
    Liu, Xuxun
    Liu, Xiao
    COMPUTER COMMUNICATIONS, 2020, 161 : 375 - 386
  • [50] Adaptive Replication for Mobile Edge Computing
    Chang, Wan-Chi
    Wang, Pi-Chung
    IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, 2018, 36 (11) : 2422 - 2432