{"title":"有效的神经网络方法用于图像识别和控制","authors":"G. Ososkov","doi":"10.1109/PHYCON.2003.1236825","DOIUrl":null,"url":null,"abstract":"A new approach to structuring and training of feed-forward artificial neural networks (ANN) is proposed. That leads to overcome many shortcomings of multilayer perceptrons and ANNs with radial basis functions (RBF-nets). A dynamical training algorithm is developed in order to keep the optimal number of neurons in the hidden layers and to guarantee the finiteness of the training procedure due to individual training of each neuron. Results of applying of the proposed neural network to recognizing frontal images of human faces look very promising and give rise to propose a non-expensive security system.","PeriodicalId":438483,"journal":{"name":"2003 IEEE International Workshop on Workload Characterization (IEEE Cat. No.03EX775)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2003-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Effective neural network approach to image recognition and control\",\"authors\":\"G. Ososkov\",\"doi\":\"10.1109/PHYCON.2003.1236825\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A new approach to structuring and training of feed-forward artificial neural networks (ANN) is proposed. That leads to overcome many shortcomings of multilayer perceptrons and ANNs with radial basis functions (RBF-nets). A dynamical training algorithm is developed in order to keep the optimal number of neurons in the hidden layers and to guarantee the finiteness of the training procedure due to individual training of each neuron. Results of applying of the proposed neural network to recognizing frontal images of human faces look very promising and give rise to propose a non-expensive security system.\",\"PeriodicalId\":438483,\"journal\":{\"name\":\"2003 IEEE International Workshop on Workload Characterization (IEEE Cat. No.03EX775)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2003-08-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2003 IEEE International Workshop on Workload Characterization (IEEE Cat. No.03EX775)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PHYCON.2003.1236825\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2003 IEEE International Workshop on Workload Characterization (IEEE Cat. No.03EX775)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PHYCON.2003.1236825","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Effective neural network approach to image recognition and control
A new approach to structuring and training of feed-forward artificial neural networks (ANN) is proposed. That leads to overcome many shortcomings of multilayer perceptrons and ANNs with radial basis functions (RBF-nets). A dynamical training algorithm is developed in order to keep the optimal number of neurons in the hidden layers and to guarantee the finiteness of the training procedure due to individual training of each neuron. Results of applying of the proposed neural network to recognizing frontal images of human faces look very promising and give rise to propose a non-expensive security system.