Du, Huiqian; Mei, Wenbo; Li, Desheng Classification of remote sensing images using BP neural network with dynamic learning rate. (Chinese. English summary) Zbl 0938.68137 J. Beijing Inst. Technol., Chin. Ed. 18, No. 4, 485-488 (1998). Summary: Backpropagation neural network classifier can solve the problems existing in the traditional classifiers and has been gradually used in the classification of remote sensing image. A new improved BP method of classifying the remote sensing image is presented. Conjugate gradient with line search was introduced to optimize the learning rate. The training speed is much higher than other methods to save time from 5 to 110s. The method avoids the burden of the large storage and the divergence of the error function so that it is that it is applicable to remote sensing image classification. MSC: 68U10 Computing methodologies for image processing Keywords:backpropagation neural network classifier; remote sensing image PDF BibTeX XML Cite \textit{H. Du} et al., J. Beijing Inst. Technol., Chin. Ed. 18, No. 4, 485--488 (1998; Zbl 0938.68137)