研究改进的YOLOV7-SSWD数字计数器读数识别算法
Zhenguan Cao1, Haixia Yang1, Liao Fang1
1School of Electrical and Information Engineering, Anhui University of Science and Technology, Huainan 232001, Anhui, China.
The Review of scientific instruments
|September 9, 2024
概括
本研究介绍了YOLOV7-SSWD模型,用于改进检查机器人的计数器读数识别. 这种新的方法提高了检测准确度和定位,这对于自动化任务至关重要.
科学领域:
- 计算机视觉 计算机视觉
- 机器人技术 机器人技术 机器人技术
- 机器学习 机器学习
背景情况:
- 在机器人检查任务中,计数器读数识别至关重要.
- 现有的算法存在低检测准确度和不准确的定位问题.
- 需要强大而精确的计数器读数识别系统.
研究的目的:
- 提出一种新的检测模型,YOLOV7-SSWD,以提高仪表读数识别精度和定位.
- 为了提高YOLOV7-Tiny模型的性能,使用多头注意力机制.
- 为检查机器人提供可靠的自动计量器读数解决方案.
主要方法:
- 通过改进YOLOV7-Tiny模型,开发了YOLOV7-SSWD.
- 整合了Wise-IoU损失功能,以解决样本质量不平衡的问题.
- 引入了SiLU激活功能以增强泛化和SimAM以改进特征提取.
- 实现了用于多尺度特征融合的动态检测头部.
主要成果:
- YOLOV7-SSWD模型实现了平均平均精度 (mAP) 的89.8%,F1得分为0.84.
- 与原始网络相比,mAP增加了8.1%,F1得分增加了0.1.
- 废弃实验验证了每个拟议组件的有效性.
结论:
- YOLOV7-SSWD算法显著提高了计数器读数的定位和识别精度.
- 拟议的模型为部署检查机器人用于自动计量器读取提供了有价值的参考.
- 提高性能有助于实现更可靠,更有效的机器人检查系统.
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