Multi-sensor Data Fusion Based on Dynamic Fuzzy Neural Network

被引：0
|
作者：
Xiao, Yang [1 ]
Cao, Zhiguo [1 ]
Zheng, Yi [1 ]
Yan, Ruicheng [1 ]
机构：
[1] Huazhong Univ Sci & Technol, Inst Pattern Recognit & Artificial Intelligence, Wuhan 430074, Peoples R China
来源：
2008 IEEE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOLS 1-8 | 2008年
关键词：
D O I：
10.1109/IJCNN.2008.4634311
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, a multi-sensor data fusion method based on dynamic fuzzy neural network(DFNN) for object recognition is proposed. DFNN is composed of two individual fuzzy neural networks. During the practical recognition process, one fuzzy neural network is used for recognition while the other is tracking trained. At the appropriate time the role of the two networks ran be exchanged according to certain switching rule. The fusion recognition system is composed of two layers. At the first layer, the features extracted from middle wave and long wave infrared images are fused by DFNN to detect potential regions which may contain objects. And then the features extracted from visible image are utilized to make recognition in these potential regions based on DFNN at the second layer. The experiment demonstrates the efficiency of the proposed method.
引用
收藏
页码：3590 / 3594
页数：5
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