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This paper proposes an occluded face detection technology based on the Adaboost algorithm. In this paper, we select moving regions for detection using a background subtraction method. The upper half and lower half parts of human face are detected respectively in moving regions by facial detector which was trained based on Adaboost algorithm and Haar features. Our experimental results indicate the...
Medium-sized enterprises (SMEs) play important role in regional economic development. It is necessary for regional educational institutes that have economics and commerce, business and finance majors to establish curriculums that have close corporation with SMEs. This relationship can help college students, faculty, and sectors in SMEs to work on commonly interested subject, especially R&D. Based...
Training classifiers on skewed data can be technically challenging tasks, especially if the data is high-dimensional simultaneously, the tasks can become more difficult. In biomedicine field, skewed data type often appears. In this study, we try to deal with this problem by combining asymmetric bagging ensemble classifier (asBagging) that has been presented in previous work and an improved random...
The echo-state-network approach for training recurrent neural networks can yield good results. However, the results depend on the experience of neural network design. It usually requires multiple tests and random chances. Through our study of the effects of spectral radius of the internal weight matrix on the training results, we propose to develop a method that can improve the echo-state network...
Most of microarray data sets are imbalanced, i.e. the number of positive examples is much less than that of negative, which will hurt performance of classifiers when it is used for tumor classification. Though it is critical, few previous works paid attention to this problem. Here we propose embedded gene selection with two algorithms i.e. EGSEE (Embedded Gene Selection for EasyEnsemble) and EGSIEE...
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