Title:
Image_Feature_Selection_Method_Based_on_Immune_Enc
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Description: Aiming at two classes image pattern recognition problem of object and background , a novel image feature selection method ,named immune antibody construction algorithm ( IACA) is proposed , inspired by the biological immune antibody encoding principle. In the case of sample parameter estimation , IACA considers entropy to measure individual feature’s sensitivity of object and background ,and defines the inclusion and complementary formulas about multi features in set theory perspective. Guided by the minimum energy principle , image immune antibody construction rules and corresponding algorithm are proposed to find an
optimized feature subset as object immune antibody. Furthermore ,the dimension of the subset can be automatically determined with out prior setting. The induction proved the result was the optimal feature subset. Data testing result shows that IACA has a lower computational complexity and error recognition rate than other methods ,which has verified the superiority and t
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基于免疫编码的图像特征选择方法.pdf
