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Deep learning methods have significantly improved classification accuracy in different areas such as speech, object and text recognition. However, this field has only began to be explored in the brain imaging field, which differs from other fields in terms of the amount of data available, its data dimensionality and other factors. This paper proposes a methodology to generate an extensive synthetic...
Most media access control (MAC) protocols can be classified as contention based or controlled based according to their transmission mechanisms. To classify contention based or control based MAC protocols in an unknown primary network, we choose received power mean and variance as two features for support vector machines (SVMs) in a machine learning based algorithm. The data consisting of these two...
Security detections for networked manufacturing can improve availability of security configuration and also lower life cycle cost. But the threat level should be classified scientifically before a safety decision could be given. In this paper, a new machine learning method suitable for small-sample pattern recognition, called least squares support vector machine, is studied, and the optimization method...
This paper proposes a new face recognition approach by using Independent Component Analysis (ICA) and Ensemble Classifiers based on Support Vector Machine (SVM). Firstly, to improve the quality of the face images, a series of image pre-processing techniques are used. Then the ICA based on Kernel Principal Component Analysis (KPCA) and FastICA is employed to extract features. At last, appropriate classifiers...
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