内蒙古民族大学学报（自然科学版）2016，Vol.31Issue(1)：31-35,5.DOI:10.14045/j.cnki.15-1220.2016.01.009
改进的遗传神经网络特征提取和分类应用
Improved Genetic Neural Network for Feature Extraction and Classification
摘要
Abstract
An improved genetic neural network is proposed in this paper:combined genetic algorithm and BP neural network,Levenberg-Marquadt algorithm is added to the learning process.The video features of the training set are randomly extracted by genetic algorithm,then the network is trained by the training set which is used to extract fea-tures,and the network is refined by LM,the feature subset is obtained so as to optimize the network structure.The net-work is applied to video feature extraction and tampering video classification,experimental results show that the net-work can effectively filter out the salient feature and get optimal feature subset,it is possible to quickly classify of tam-pering videos.关键词
神经网络/遗传算法/特征提取Key words
Neural networks/Genetic algorithms/Feature extraction分类
信息技术与安全科学引用本文复制引用
陈雪艳..改进的遗传神经网络特征提取和分类应用[J].内蒙古民族大学学报（自然科学版）,2016,31(1):31-35,5.基金项目
国家自然科学基金资助项目(61440041) （61440041）
