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In this paper, we consider the identification of systems based on binary measurements of the output. The linear part of the system is parameterized by a Finite Impulse Response filter and the binary sensor is parameterized by a threshold. The idea is to formulate the identification problem as a classification problem. This formulation allows the use of supervised learning algorithm such as Support...
Many people share their daily events and opinions on Twitter. Some tweets are beneficial and others are related to such aspects of a user's real life as eating, traffic conditions, weather, and so on. In this paper, we propose an inference method of the real life aspect distribution of tweets using a labeled tweets. Our method infers the aspect probability distributions by a hierarchical estimation...
Existing age estimation algorithms based on facial images have been showing high dependency on the age range with the range 29–49 yielding the best estimation results. This paper introduces a new multi-stage binary age estimation (MSAE) system configured as a network of decision making neural network (NN) and support vector machine (SVM) units. The decision making process was based on the classification...
Density distribution is an important coal quality index used in the coal industry. The traditional method is excessively complex and time-consuming. Therefore, a new and fast method for coal density distribution estimation by weight is proposed. A semi-automatic local-segmentation algorithm and a multi-scale image segmentation algorithm based on a Hessian matrix were used to identify coal particles...
Haze and mist always affect the quality of vision. If an image is suffered from haze or mist, then the object is unclear and the image seems whiter than the original one. There are several haze removal algorithms that can reduce the effect of haze and mist. However, if an image is not suffered from the haze and mist, applying the haze removal algorithm may darken the image. Therefore, in computer...
As a methodology for automatic detection of Parkinson's disease (PD), it is proposed the estimation of the different glottal flow features considering nonlinear behavior of the vocal folds. This paper evaluates the discrimination capability of set with eight different Nonlinear Dynamic (NLD) features. The experiment presented considering the five Spanish vowels uttered by 50 People with PD (PPD) and...
Fetal heart rate monitoring plays an essential role in helping to decrease the perinatal mortality rate associated with abnormalities in the cardiovascular system of the fetus. In this sense, a new approach to detect fetal QRS (fQRS) complexes from abdominal maternal ECG signals is proposed in this paper. First, signals were segmented into contiguous frames of 250 ms duration and then labeled in four...
In this article we present a fusion architecture for the automatic classification of sleep stages. The architecture relies on time and frequency domain features which are processed by dissimilar classifiers. The initial predictions of each classifier are refined by using fusion of the prediction estimations together with temporal contextual information of the electroencephalographic signal. The experimental...
Aging is the process of changing the status of human body which human face shows the most important changes. One of the most challenges of age estimation methods is feature extraction which the feature extraction method is failed to extract full informative feature vector elements in the case of deformation, scaling,… in image. So, a feature extractor which is robust against to the situations is necessary...
In this research work, we demonstrate state-of-charge (SoC) estimation using support vector regression (SVR) approach for a high capacity Lithium Ferro Phosphate (LiFePO4) battery module. The proposed SoC estimator in this work is extracted from open circuit voltage (OCV)-SoC lookup table which is obtained from the battery module discharging and charging testing cycles, using voltage and current as...
Human-crowd density estimation problem has always been difficult when the scenario is affected by strong perspective distortion and high occlusion. However, this difficulty can be mitigated by the indirect counting approach, i.e. counting them without actually detecting them. Based on this approach, Qing Wen et al. proposed a method relies on the texture features extraction using Gabor filters and...
Human body orientation estimation is useful for analyzing the activities of a single person or a group of people. Estimating body orientation can be subdivided in two tasks: human tracking and orientation estimation. In this paper, the second task of orientation estimation is accomplished by using HoG descriptors and other cues such as the velocity direction, the presence of face, and temporal smoothness...
In this paper, we propose a quality of experience (QoE) estimation model for HTTP video streaming service over wireless networks. In the proposed model, the comprehensive QoE influence factors are grouped into two types, namely the objectivity-aware parameters and the psychology-aware parameters. The considered factors include video content features, the encoding parameters, the network transmission...
Ranking algorithms have proven the potential for human age estimation. Currently, a common paradigm is to compare the input face with reference faces of known age to generate a ranking relation whereby the first-rank reference is exploited for labeling the input face. In this paper, we proposed a framework to improve upon the typical ranking model, called Voting system on Ranking model (VRank), by...
Due to the deregulation of the power system, the electric power industry is undergoing a transformation in terms of its planning and operation strategies. Because of the importance in reducing financial and operational risk, improving load forecasting accuracy is paramount. In some load forecasting applications, K-means clustering is used to group customers prior to forecasting. This method has been...
Despite the abnormal patterns recognition and mean shift size estimation of control chart signals could provide some evidence for statistical process diagnostics, it do not reveal the real time of the process changes, which is essential for identifying assignable causes and ultimately ensure stability of process. In this paper, a support vector machine based multi-kernel (MK-SVM) method for change...
Reconstruction problem for signals generated by discrete nonlinear dynamic system is considered via unified approach to recurrent kernel-based dynamic systems. In order to prevent the model complexity increasing under on-line identification, the reduced order model kernel method is proposed and proper recurrent Least-Square identification algorithms are designed along with conventional regularization...
We present a novel approach to automated estimation of agreement intensity levels from facial images. To this end, we employ the MAHNOB Mimicry database of subjects recorded during dyadic interactions, where the facial images are annotated in terms of agreement intensity levels using the Likert scale (strong disagreement, disagreement, neutral, agreement and strong agreement). Dynamic modelling of...
In this paper, we propose a technique for the automatic recognition of "fake" stereoscopic videos/movies i.e., videos which result from classic 2D videos through a 2D to 3D conversion process. Essentially, the proposed technique distinguishes between 2D movies converted to 3D and real stereoscopic ones. It is based on the difference in sharpness around foreground objects in a converted stereo...
Monocular visual odometry is an active research topic for mobile robot navigation due to its availability and simpleness. However, it inherently suffers from scale ambiguity inherently, so that the precesion of odometry becomes poor. In this paper, we propose a new method to resolve scale ambiguity for monocular visual odometry based on ground area extraction and a modified adaptive kalman-filter...
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