计算机科学 ›› 2021, Vol. 48 ›› Issue (6A): 63-66.doi: 10.11896/jsjkx.200900163
胡京徽, 许鹏
HU Jing-hui, XU Peng
摘要: 随着我国航空紧固件制造业的高速发展,生产车间流水线上的紧固件制造工艺变得越来越复杂。目前,生产流水线上工段内中不同规格产品的流转停留在人工分类阶段,这种做法不仅耗费人力,还很难满足实时处理分类需求。文中提出一种基于图像分类算法的航空紧固件自动分类方法,设计了一套紧固件图像采集和自动分类实施方案,并根据真实工业数据执行评估实验,评估实验统计了卷积神经网络和Inception-v3模型的准确率、查全率、查准率和F1值指标。实验结果表明,Inception-v3的各项评估指标优于卷积神经网络,Inception-v3模型分类的准确率达到98%以上,可以有效对航空紧固件产品实现自动分类。
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