计算机技术与发展2024，Vol.34Issue(10)：126-133,8.DOI:10.20165/j.cnki.ISSN1673-629X.2024.0190
基于注意力网络集成的联机空中手写识别研究
An Attention Network Ensemble-based Study of Online in Air-writing Recognition
摘要
Abstract
Aiming at the problems of small data samples,insufficient model generalization ability and low recognition rate of online In Air-Writing recognition,an ensemble-based online In Air-Writing recognition method was proposed.Firstly,the original multi-dimensional data was constructed by incorporating"online"time series features into the shape features,and the multi-dimensional fusion data was projected to three orthogonal planes to obtain three sets of projection features.Secondly,a convolutional neural network was constructed to extract the visual features,next character embedding was introduced as class labels of the image,and the class-labelled character-level semantic features were fused with the three sets of visual features through the attention detection mechanism to form three sets of semantically informative feature maps,and a SoftMax classifier was constructed based on the feature maps.Finally,the classification and recognition was performed by the main learner-based integrated voting method.Multiple sets of experiments were carried out on two sets of In Air-Writing datasets and the HIT-OR3C online dataset,and in the case of small sample recognition,the rec-ognition rates of the proposed method were better than that of other methods,which were 95.68%,93.02%and 94.96%respectively.The experimental result showed that the proposed method fully explored the effective features in the In Air-Writing data under the condition of small sample data,and improved the efficiency of In Air-Writing recognition.关键词
空中手写/联机手写/小样本学习/数据融合/注意力网络/集成学习/手势识别Key words
In Air-Writing/On-Line Writing/small sample learning/data fusion/attention network/ensemble learning/gesture recogni-tion分类
信息技术与安全科学引用本文复制引用
张墨逸,邢蕾,叶洪昶,陈海燕..基于注意力网络集成的联机空中手写识别研究[J].计算机技术与发展,2024,34(10):126-133,8.基金项目
国家自然科学基金项目(62161019) （62161019）
