A Review on Back-Propagation Neural Networks in the Application of Remote Sensing Image Classification

作     者：Alaeldin Suliman Yun Zhang 

作者机构：Department of Geodesy and Geomatics Engineering University of New Brunswick Fredericton E3B-5A3 Canada 

出 版 物：《Journal of Earth Science and Engineering》 (地球科学与工程（英文版）)

年 卷 期：2015年第5卷第1期

页      码：52-65页

摘      要：ANNs （Artificial neural networks） are used extensively in remote sensing image processing. It has been proven that BPNNs （back-propagation neural networks） have high attainable classification accuracy. However, there is a noticeable variation in the achieved accuracies due to different network designs and implementations. Hence, researchers usually need to conduct several experimental trials before they can finalize the network design. This is a time consuming process which significantly reduces the effectiveness of using BPNNs and the final design may still not be optimal. Therefore, there is a need to see whether there are some common guidelines for effective design and implementation of BPNNs. With this aim in mind, this paper attempts to find and summarize the common guidelines suggested by different authors through literature review and discussion of the findings. To provide readers with background and contextual information, some ANN fundamentals are also introduced.

主 题 词：Artificial neural networks back propagation classification remote sensing. 

学科分类：12[管理学] 0810[工学-土木类] 1201[管理学-管理科学与工程类] 081104[081104] 08[工学] 0835[0835] 081002[081002] 0811[工学-水利类] 0812[工学-测绘类] 

馆 藏 号：203782146...