Abstract
In the target detection technology in the field of computer vision, the small sample target detection technology has a small number of samples and insufficient feature extraction ability, resulting in low detection rate and over-fitting. In this paper, a false alarm removal method for small sample target detection is proposed. The Haar +Adaboost algorithm is used for preliminary detection, and the false alarm target is removed by SVM to improve the accuracy of detection. The experimental results show that the accuracy of the small sample target detection is indeed improved, and the detection speed is also faster.
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