边缘AI的霜雪识别系统设计与实现
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1.南京信息工程大学电子与信息工程学院,江苏南京 210044;2.南京信息工程大学滨江学院,江苏无锡214105;3.南京信息工程大学江苏省大气环境与装备技术协同创新中心,江苏南京210044;4.江苏省无线电研究所有限公司,江苏无锡,214073

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TP2

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南京信息工程大学滨江学院课题资助,项目编号:2019bjyng006;国家自然科学基金(61601229)


Design and Implementation of frost and snow recognition system for edge AI
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1.College of Electronic and Information Engineering, Nanjing University of Information Science & Technology, Nanjing, Jiangsu 210044,China; 2.Binjiang College, Nanjing University of Information Science & Technology, Nanjing, Jiangsu 210044, China;3.Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science and Technology, Nanjing, Jiangsu 210044, China;4.Jiangsu Radio Research Institute Co. LTD,Wuxi, Jiangsu 214073, China

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    摘要:

    为提高霜雪识别系统的识别率,开展了基于边缘AI的霜雪识别系统设计。综合海思嵌入式处理器Hi3559A高算力、低功耗特点,硬件部分采用模块复用的方法降低功耗和资源消耗,软件部分,从模型训练、模型量化、模型部署入手对MobileNetV2图像分类网络和ISP自适应处理算法进行改进,最终识别率99.7%,预处理时间0.3s,图像分类时间0.8s,模组平均功率2W,鲁棒性好、性能稳定。由此可见Hi3559A智能相机模组可有效纠正雪深探测仪的疑误数据。

    Abstract:

    In order to improve the recognition rate of the frost and snow recognition system, a frost and snow recognition system powered by edge AI was designed. The design comprised the character of Hi3559A both excellent computation and low power consumption. The hardware used reduce power and resource consumption by Module reuse. For the software, by integrating the characteristics of the high computing power of Hisi, embedded processors Hi3559A and IMX334, and starting from model training, model quantization and model deployment, the author improved the MobileNetV2 image classification network and ISP adaptive processing algorithm. The final recognition rate reached 99.7%, pre-processing time reached 0.3s, image classification time reached 0.8s, module average power was 2W, and has its properties being robustness and stable. Hence,the Hi3559A intelligent phase machine module can effectively correct the inaccuracy of the data from the snow depth detector.

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胡敏,裴晓芳,顾平月,花卫东.边缘AI的霜雪识别系统设计与实现[J].电子测量技术,2021,44(1):142-149

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  • 在线发布日期: 2024-12-31
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