摘要
针对ICM模型用于目标识别参数需要人工设置的问题,提出一种新的ICM模型参数设置方法。该方法从提高目标识别率出发,提出利用相关系数确定ICM模型参数学习准则,使用梯度下降法对这一准则进行求解,达到根据输入图像的不同自适应确定ICM模型参数的目的。实验结果表明该方法可以很好解决传统ICM网络参数需要人工选取的劣势。
In identifiying targets,the parameters of the ICM model need to be set manually.So we propose what we believe to be a new and effective method for setting the parameters,which is explained in sections 1 and 2 of the full paper.Section 1 briefs the ICM.Subsections 2.1 deals with the error function,which is based on correlation coefficients,and the ICM parameteer setting procedures based on gradient descent;subsection 2.2 gives a 3-step calculation procedure for adaptively setting the ICM parameters in accordance with different input images.Section 3 uses three numerical examples to verify the effectiveness of our method;the simulation results,given in Figs.1 through 3 and Tables 1 and 2,and their analysis show preliminarily that our new method has slightly higher target recognition rate than the method mentioned in Ref.11 and can indeed effectively set the ICM parameters and enhance the reliability and efficiency of the ICM.
出处
《西北工业大学学报》
EI
CAS
CSCD
北大核心
2012年第2期201-205,共5页
Journal of Northwestern Polytechnical University
基金
国家自然科学基金(61101191)
陕西省自然科学基金(2011JQ8016)
西北工业大学基础研究基金
航空科学基金(20100153001)资助
关键词
交叉皮层模型
图标
误差函数
梯度下降
目标识别
algorithms
analysis
calculations
correlation methods
effects
efficiency
feature extraction
functions
image processing
models
numerical methods
optimization
parameter estimation
reliability
simulation
standards
targets
error function
gradient descent
intersecting cortical model（ICM）
target recognition
icon
