We propose a general method applicable to existing multi- class boosting-algorithms for creating cascaded classifiers. The motiva- tion is to introduce more ...
Abstract. We propose a general method applicable to existing multiclass boosting-algorithms for creating cascaded classifiers.
We propose a general method applicable to existing multiclass boosting-algorithms for creating cascaded classifiers. The motivation is to introduce more ...
We propose a general method applicable to existing multiclass boosting-algorithms for creating cascaded classifiers. The motivation is to introduce more ...
We present new ensemble learning algorithms for multi-class classification. Our algorithms can use as a base classifier set a family of deep decision trees ...
Missing: Cascades | Show results with:Cascades
By implementing a multiclass cascaded classifier with AdaBoost, we show how detection runtimes are accelerated since only a subset of the ensemble is executed, ...
We present new ensemble learning algorithms for multi-class classification. Our algorithms can use as a base classifier set a family of deep decision trees ...
A method was developed which enabled the cascaded classifiers to efficiently adapt to the changing environment on domains with high volume streaming data. This ...
The paper demonstrates how popular, non-cascaded algorithms like AdaBoost.M2, AdaBoost.OC and AdaBoost.ECC can be converted into robust cascaded classifiers.
The paper demonstrates how popular, non-cascaded algorithms like AdaBoost.M2, AdaBoost.OC and AdaBoost.ECC can be converted into robust cascaded classifiers.