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This paper presents an appearance feature based facial expression recognition system using Kohonen Self-Organizing Map (KSOM). Appearance features are extracted using uniform Local binary patterns (LBPs) from equally sub-divided blocks applied over face image. The dimensionality of the LBP feature vector is further reduced using principal component analysis (PCA) to remove the redundant data that...
The paper presents a facial expressions recognition system using Bayesian network. We train the network using probabilistic modeling that draws relationship between facial features, action units and finally recognizes six basic emotions. We propose features extraction methods to get geometric feature vector containing angular informations and appearance feature vector containing moments extracted...
Identifying and understanding the impact of algorithmic trading on financial markets has become a critical issue for market operators and regulators. Advanced data feed and audit trail information from market operators now make the full observation of market participants' actions possible. A key question is the extent to which it is possible to understand and characterize the behavior of individual...
One of the leading diseases in women is breast cancer. The detection in an earlier stage is done by indicating the presence of architectural distortion (AD). An AD detection system with support vector machine is developed in this research. The 15 features are extracted from the fuzzy co-occurrence matrix and fractal dimension. The principal component analysis is also implemented to help in feature...
Support Vector Machine (SVM) is a well-known kernel-based method for binary classification problem. SVM aims at constructing the optimal middle hyperplane which induces the largest margin. It is proven that in a linearly separable case, this middle hyperplane offers the high accuracy on universal datasets. However, real world datasets often contain overlapping regions and therefore, the decision hyperplane...
Researches on office building energy consumption have been hot in these years, but few researchers consider the classification of office energy consumption performance which can evaluate user behaviors in order to offer a clear analysis of energy consumption and improve their energy saving consciousness. In this paper, we propose a novel hierarchical classification algorithm for evaluating energy...
The problem of classifying imbalanced datasets has drawn a significant amount of interest from academia and industry. In this paper, we propose a modified support vector machine (SVM) approach using conformal kernel transformation to address the class imbalance problem. The proposed method first uses standard SVM algorithm to obtain an approximate hyperplane. And then, we give a kernel function and...
Neuroscientists usually determine similarity between EEG electrode signals, by a measure of pairwise linear dependence among them. However, recent research indicates the drawbacks of analyzing the pairwise dependence of signals instead of analyzing the simultaneous joint interdependence among them. To overcome this problem we propose a novel similarity measure known as probabilistic relative correlation...
This research focuses on the development of a realtime intelligent facial emotion recognition system for a humanoid robot. In our system, Facial Action Coding System is used to guide the automatic analysis of emotional facial behaviours. The work includes both an upper and a lower facial Action Units (AU) analyser. The upper facial analyser is able to recognise six AUs including Inner and Outer Brow...
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