现代信息科技2024，Vol.8Issue(18)：39-42,47,5.DOI:10.19850/j.cnki.2096-4706.2024.18.008
基于手势识别的DeepLabV3+算法研究
Research on DeepLabV3+ Algorithm Based on Gesture Recognition
摘要
Abstract
In order to solve the problems that multi-temporal and feature diversity are not considered in gesture recognition research,this paper proposes a gesture recognition extraction method based on improved DeeplabV3+model.By changing the ASPP module structure in the model,using multiple different void rates and image Pyramid Pooling and other operations,CBAM Attention Mechanism modules are added to improve the extraction accuracy and efficiency of the model.The results show that the training speed of improved DeeplabV3+model is improved by 29.2%,the recognition accuracy is improved by 0.04%,the similarity is improved by 0.68%,and the recall rate is improved by 0.36%.关键词
语义分割/手势识别/深度学习/DeepLabV3+模型Key words
semantic segmentation/gesture recognition/Deep Learning/DeepLabV3+model分类
信息技术与安全科学引用本文复制引用
王宇,潘景浩,巫朝明,陈宗岩,王雅宁,谢跃..基于手势识别的DeepLabV3+算法研究[J].现代信息科技,2024,8(18):39-42,47,5.基金项目
2023年"南京工程学院大学生创新训练项目计划"(省级)(202311276082Y) （省级）
