JI Xin, CHEN Jianyun, WANYAN Xingxing. Improved VGG-16 model for visual OCS earthing recognition[J]. 2021, (2): 58-60+72. DOI: 10.13873/J.1000-9787(2021)02-0058-03.
用于接触网可视化接地识别的改进VGG—16模型
摘要
针对由于人为及外界复杂环境因素的干扰
接触网可视化接地系统的视频图像识别率较低的问题
提出了一种经结构简化与改进的VGG—16深度网络模型。通过迁移学习策略获得了良好的特征提取能力
结合稀疏自编码器(SAE)优化卷积特征
使网络具有一定的稀疏性
提升模型识别精度和泛化能力
又使训练参数减少。实验结果表明:该模型在验证集上达到了92%的识别率。
Abstract
Aiming at the problem of low recognition rate of video image of visual over contact system( OCS)earthing system of connection network due to the interference of human and complex environmental factors
a simplified and improved VGG—16 model for depth network is proposed. Benefit from the transfer learning strategy
good feature extraction ability is obtained
and convolution feature is optimized by sparse automatic encoder( SAE)
which makes the network sparse
it also improves the recognition precsion and generalization ability
reduces training parameters. The model achieves recognition rate of 92 % on validation set.