摘要
构建了一种用于图像目标识别的多层前向神经网络,给出了网络拓扑结构,并成 功地把该神经网络运用到车型识别中。该方法综合了神经网络、模糊逻辑、模式识别的相 关 算法,对图像目标轮廓进行整体识别,达到了较高的目标识别准确率。实践表明,该网 络经 过监督学习后,能摒除图像中一定量干扰像素影响,准确地识别出各种外形车的车型 。
This paper proposes a forward multi-layer neural network model which can be used for object recognition in images, and presents the models network t opology , which has put neural nework into the vehicle shape recognition succe ss fully. The model integrates some results of neural network,fuzzy logic ,patt ern recognition etc.,and recognizes the object in the image wholly . The practi ce i n the car-type recognition using the model proves that through supervised-l earni ng , this model can correctly recognize the vehicle shape in spite of some inter ferential Pixels.
出处
《计算机工程》
CAS
CSCD
北大核心
2003年第3期30-32,共3页
Computer Engineering