舰船电子工程2019，Vol.39Issue(10)：52-56,5.DOI:10.3969/j.issn.1672-9730.2019.10.012
基于SSD-Mobilenet模型的目标检测
Target Detection Based on SSD-Mobilenet Model
刘颜 1朱志宇 1张冰1
作者信息
- 1. 江苏科技大学电子信息学院 镇江 212003
- 折叠
摘要
Abstract
In order to shorten the training time of the model and speed up the rate of the convergence of the network during the target detection,this paper adopts a method combining convolutional neural network and transfer learning.The detection speed of the SSD network is fast and the mobilenet lightweight network takes up less memory. SSD-Mobilenet model combines the advantages of SSD network and Mobilenet network. Firstly,the SSD-Mobilenet model is pre-trained with the COCO dataset to obtain the pa?rameters and bottleneck description factors of the model. Then the Pets dataset is used to retrain the full connection layer of the net?work. Using the idea of transfer learning,the model can converge in a short time with small datasets. The experimental results show that the total training time is about 11 hours,and the detection accuracy reaches 74.5%. This shows that the method combined with SSD-Mobilenet model and transfer learning can shorten the training time of the model,accelerate the convergence speed of the mod?el and have a high detection accuracy.关键词
目标检测/卷积神经网络/SSD-Mobilenet/迁移学习Key words
target detection/convolutional neural networks/SSD-Mobilenet/transfer learning分类
信息技术与安全科学引用本文复制引用
刘颜,朱志宇,张冰..基于SSD-Mobilenet模型的目标检测[J].舰船电子工程,2019,39(10):52-56,5.
