Remote sensing image classification algorithm based on hopfield neural network

Authors:
Guang-jun Dong;Yong-sheng Zhang;Chao-jie Zhu
Affiliations:
Information Engineering University Institute of Surveying and Mapping, Zhengzhou, China;Information Engineering University Institute of Surveying and Mapping, Zhengzhou, China;Information Engineering University Institute of Surveying and Mapping, Zhengzhou, China
Venue:
ISNN'06 Proceedings of the Third international conference on Advnaces in Neural Networks - Volume Part II
Year:
2006

Citing 3
Cited 0

HAVNET: a new neural network architecture for pattern recognition

Neural Networks
Neural Networks: A Comprehensive Foundation

Neural Networks: A Comprehensive Foundation
High Storage Capacity Architecture for Pattern Recognition Using an Array of Hopfield Neural Networks

AIPR '01 Proceedings of the 30th on Applied Imagery Pattern Recognition Workshop

Quantified Score

Hi-index	0.00

Visualization

Abstract

Considering the feature of remote sensing images, we put forward a remote sensing image classification algorithm based on Hopfield neural network. First, the function and principle of Hopfield neural network is described in this paper. Then based on the common model of Hopfield neural network, the image classification algorithm using Hopfield neural network is realized and experimental results show that its precision is superior to that of the conventional maximum likelihood classification algorithm.