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In this paper, we demonstrate nonlinear features extracted by deep neural network have better results in the task of dictionary learning. A nonlinear dictionary learning model is constructed and the optimization algorithm is developed. In the learning algorithm, we use the deep neural network to convey raw samples to feature space and learn a nonlinear dictionary. The extensive experimental results...
To diagnose performance problems in production systems, many OS kernel-level monitoring and analysis tools have been proposed. Using low level kernel events provides benefits in efficiency and transparency to monitor application software. On the other hand, such approaches miss application-specific semantic information which can be effective to differentiate the trace patterns from distinct application...
In the field of computer vision, image matching is very important in many applications, such as the object recognition, 3D reconstruction, stereo vision, motion tracking and augmented reality. A method of improving the Opensurf algorithm used in AR for decreasing matching points and mismatch and increasing the calculation speed is proposed.
Feature representation and classification are two key steps for face recognition. A novel method for face recognition was presented based on combination of PCA (principal component analysis), LDA (linear discriminate analysis) and SVM (support vector machine). PCA and LDA combination was used for feature extraction and SVM were used for classification. The normalization had been done to eliminate...
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