A novel confidence estimation method for neural networks in multispectral image classification

作     者：O.Arslan 

作者机构：Geodesy and Photogrammetry Engineering DepartmentEngineering FacultyUniversity of Kocaeli41040Turkey 

出 版 物：《International Journal of Digital Earth》 (国际数字地球学报（英文）)

年 卷 期：2009年第2卷第4期

页      面：343-358页

核心收录：

学科分类：0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 

主　　题：digital earth neural networks confidence estimation image classification 

摘      要：The Digital Earth concept has attracted much attention recently and this approach uses a variety of earth observation data from the global to the local *** techniques have made much progress technically and the methods used for automatic extraction of geo-ralated information are of importance in Digital Earth *** of these methods,artificial neural networks(ANN)techniques,have been effectively used in classification of remotely sensed *** image classification with ANN has been producing higher or equal mapping accuracies than parametric *** studies have,in fact,shown that there is no discernible difference in classification accuracies between neural and conventional statistical *** well designed and trained neural networks can present a better performance than the standard statistical *** are,as yet,no widely recognised standard methods to implement an optimum *** this point of view it might be beneficial to quantify ANN’s reliability in classification *** measure the reliability of the neural network might be a way of developing to determine suitable network *** date,the problem of confidence estimation of ANN has not been studied in remote sensing studies.A statistical method for quantifying the reliability of a neural network that can be used in image classification is investigated in this *** this purpose the method is to be based on a binomial experimentation concept to establish confidence *** novel method can also be used for the selection of an appropriate network structure for the classification of multispectral *** the main focus of the research is to estimate confidence in ANN,the approach might also be applicable and relevant to Digital Earth technologies.