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Processing feature recognition based on improved YOLOv5 algorithm

delete2025-09-04
delete0
PRE
AI
L
Liqin Miao
J
Jialong Li
冯鑫 封面图
冯鑫 (Xin Feng) *
Z
Zhengwei Tang
H
Huaidan Liang
DOI：10.1007/s00170-025-16266-4delete
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摘要

摘要

En 中文
加工特征识别技术能够有效集成CAD和CAPP系统，从而实现设计信息与制造信息的有效互操作性。传统的加工特征识别技术不具备学习能力，识别效率低，且识别结果的准确性无法保证，而深度神经网络技术不仅具备学习能力，其抗噪声能力还能提高识别精度；因此，所提出的基于深度学习的加工特征分类与识别技术，采用多角度降尺度方法捕捉图像中的加工特征，创建加工特征数据集，并通过改进的YOLOv5深度神经网络模型训练数据集，再使用加工特征分类器对加工零件模型进行分类并输出加工特征结果。通过结合UG平台以典型零件为例验证了加工特征识别过程，为加工特征识别技术提供了新思路。
Keyword:
Processing characteristics
Image recognition
Deep neural network
Data set

期刊

International Journal of Advanced Manufacturing Technology 封面图
International Journal of Advanced Manufacturing Technology
IF:
3.1
论文数:
2.0K
被引数:
6.4W

机构

C
College of Mechanical and Electrical Engineering
学者数:
868
论文数: 272
被引数: 0
C
College of Computer Science and Technology
学者数:
854
论文数: 298
被引数: 0
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