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- W2381032979 abstract "Improving cascade classifier based on Haar-like feature and Adaboost,this paper proposes an on-road vehicle detection method fusing Harr-like and HOG.Firstly,HOG feature is integrated into the traditional Haar-like feature set.Additionally,different weak classifiers for HOG features and Haar-like features are designed,and Gentle Adaboost algorithm is adopted to train the layer classifiers.Finally,based on the fusion features,a cascade classifier combined with Support Vector Machine is proposed.In the last few layers of the cascade,feature vectors composed by the features that selected by Gentle Adaboost algorithm are used to train robust SVM classifiers.Experimental results indicate that the proposed method can detect on-road vehicles effectively." @default.
- W2381032979 created "2016-06-24" @default.
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- W2381032979 date "2013-01-01" @default.
- W2381032979 modified "2023-09-23" @default.
- W2381032979 title "Fusing Multiple Features to Detect On-road Vehicles" @default.
- W2381032979 hasPublicationYear "2013" @default.
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