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- W2377894139 abstract "SVM has been paid more and more attention for its good classification ability in image semantic classification field.As the classification performance is decided by SVM kernel functions and parameters together,this paper analyzed the influences of different kernel functions and parameter optimization algorithms on image semantic classification performance,and verified the influences with natural landscape pictures.The experimental result shows the SVM method obtained the best semantic classification effect when the RBF kernel function was choosen and parameters were optimized by grid search method.This conclusion has reference meaning in image semantic classification." @default.
- W2377894139 created "2016-06-24" @default.
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- W2377894139 date "2011-01-01" @default.
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- W2377894139 title "Semantic Extraction of Image Using Support Vector Machines" @default.
- W2377894139 hasPublicationYear "2011" @default.
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