Paper
9 January 2024 Visual recognition and comparison system and method of intelligent watt hour meter chip based on convolutional neural network
Zhengang Shi, Chaofei Wu, Wenjie Fu, Peng Tao, Linhao Zhang, Bo Gao
Author Affiliations +
Proceedings Volume 12969, International Conference on Algorithm, Imaging Processing, and Machine Vision (AIPMV 2023); 1296921 (2024) https://doi.org/10.1117/12.3014476
Event: International Conference on Algorithm, Imaging Processing and Machine Vision (AIPMV 2023), 2023, Qingdao, China
Abstract
To enhance the performance of intelligent watt hour meters, a visual recognition and comparison system based on convolutional neural networks is proposed for intelligent watt hour meter chips. Firstly, the overall framework of the chip visual recognition comparison system is designed. Secondly, the hardware part of the system comprises the image acquisition module and image data transmission module of intelligent watt hour meter chips. In the software part, the classification function is selected based on the structural characteristics and operational principle of convolutional neural networks, and iterative training is used to complete the identification and comparison of smart meter chips. The experimental results demonstrate that this proposed system can significantly improve the accuracy of visual recognition and comparison, while also reducing the time consumption when compared to traditional recognition and comparison systems.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Zhengang Shi, Chaofei Wu, Wenjie Fu, Peng Tao, Linhao Zhang, and Bo Gao "Visual recognition and comparison system and method of intelligent watt hour meter chip based on convolutional neural network", Proc. SPIE 12969, International Conference on Algorithm, Imaging Processing, and Machine Vision (AIPMV 2023), 1296921 (9 January 2024); https://doi.org/10.1117/12.3014476
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