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In order to achieve subject-independent facial expression recognition and obtain robustness against illumination variety and image deformation, facial expression recognition methods based on Gabor wavelet transformation and elastic templates matching are presented in this paper. Firstly, given a still image containing facial expression information,(More)
Wireless Sensor Networks (WSNs) are generally used to collect information from the environment. The gathered data are delivered mainly to sinks or gateways that become the endpoints where applications can retrieve and process such data. However, applications would also expect from a WSN an event-driven operational model, so that they can be notified(More)
The key security challenges and solutions on the cloud have been investigated in this paper with the help of literature reviews and an experimental model created on OPNET that is simulated to produce useful statistics to establish the approach that the cloud computing service providers should take to provide optimal security and compliance. The literatures(More)
A neural network (NN) pruning method optimized with particle swarm optimization (PSO) algorithm is proposed in this paper. Correlation merging algorithm is an important pruning method in NN structure design. Unlike general training method with back-propagation (BP), this paper uses PSO algorithm in the pruning process. The PSO is used to optimize the(More)
—As an essential way of human emotional behavior understanding, speech emotion recognition (SER) has attracted a great deal of attention in human-centered signal processing. Accuracy in SER heavily depends on finding good affect-related, discriminative features. In this paper, we propose to learn affect salient features for SER using convolutional neural(More)
Deep learning systems, such as Convolutional Neural Networks (CNNs), can infer a hierarchical representation of input data that facilitates categorization. In this paper, we propose to learn affect-salient features for Speech Emotion Recognition (SER) using semi-CNN. The training of semi-CNN has two stages. In the first stage, unlabeled samples are used to(More)
In order to improve the recognition accuracy of speech emotion recognition, in this paper, a novel hierarchical method based on improved Decision Directed Acyclic Graph SVM (improved DDAGSVM) is proposed for speech emotion recognition. The improved DDAGSVM is constructed according to the confusion degrees of emotion pairs. In addition, a geodesic(More)