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Forensic Voice Comparison (FVC) is increasingly using the likelihood ratio (LR) in order to indicate whether the evidence supports the prosecution (same-speaker) or defender (different-speakers) hypotheses. Nevertheless, the LR accepts some practical limitations due both to its estimation process itself and to a lack of knowledge about the reliability of this (practical) estimation process. It is...
Dysarthria is a motor speech impairment, often characterized by speech that is generally indiscernible by human listeners. Assessment of the severity level of dysarthria provides an understanding of the patient's progression in the underlying cause and is essential for planning therapy, as well as improving automatic dysarthric speech recognition. In this paper, we propose a non-linguistic manner...
Natural and affective handshakes of two participants define the course of dyadic interaction. Affective states of the participants are expected to be correlated with the nature of the dyadic interaction. In this paper, we extract two classes of the dyadic interaction based on temporal clustering of affective states. We use the k-means temporal clustering to define the interaction classes, and utilize...
Sports event recognition and classification is a challenging task due to the number of possible categories. On one hand, how to characterize legitimate event classification names and how to acquire preparing tests for these classes should be investigated, then again, it is non-inconsequential to accomplish acceptable order execution. To address these issues, a content mining pipeline is initially...
The QRS detection algorithms based on properties of most cardio signals and barely sensitive to the QRS shape are considered in the paper. Signal energy and velocity of signal fluctuations are such kind of properties. The implementation of these algorithms allows to detect QRS among other ECG elements. Two new algorithms which develop the idea of widely known Pan-Tompkins algorithm are suggested....
The paper presents a comprehensive approach using clustering based data mining for load curves characterization in real distribution networks. The load curves characterized by their main indicators is made using information provided by Smart Meters. The proposed method was tested using a real database with 60 rural substations. The results demonstrate the ability of the methodology to be efficiently...
In this work, we suggest a new approach which enables the localization and the compensation of sensor fault for perturbed piecewise affine hybrid systems. In fact, we used the additive fault tolerant control to ensure the compensation of this fault. The application of this method involves two important steps. The first step, is to generate the estimated fault by using Data-based Projection Method...
In this paper we present a novel approach for 3D facial expression recognition based on a registration method. The used registration method, called the Coherent Point Drift (CPD), is applied to estimate complex non-linear and nonrigid transformation between 3D facial surfaces. The computed transformation allows to recover shape deformations that are induced by facial expression variations. Machine...
Lung segmentation in chest radiographs is a requisite pre-processing step in the Computer-aided Diagnosis (CAD) system for the detection of chest diseases. This paper proposes an unsupervised lung segmentation method in chest radiographs based on shadow filter and multilevel thresholding. The method consists of three main processes: pre-processing, initial lung field estimation and noise elimination...
Inferring scene depth from a single monocular image is an essential component in several computer vision applications such as 3D modeling and robotics. This process is an ill-posed problem. To tackle this challenging problem, previous efforts have been focusing on exploiting only global or local depth aware properties. We propose a model that incorporates both of them to obtain significantly more...
Gender estimation has received increased attention due to its use in a number of pertinent security and commercial applications. Automated gender estimation algorithms are mainly based on extracting representative features from face images. In this work we study gender estimation based on information deduced jointly from face and body, extracted from single-shot images. The approach addresses challenging...
Human age estimation is an important research topic and can find its applications in such as commodity recommendation and security monitoring. The establishment of existing estimators basically follows a same pipeline, i.e., an estimator is built from a given training dataset like FG-NET and then evaluated on a holdout testing set to determine its effectiveness. In doing so, a usually-followed assumption...
Forensic Voice Comparison (FVC) is increasingly using the likelihood ratio (LR) in order to indicate whether the evidence supports the prosecution (same-speaker) or defender (different-speakers) hypotheses. In addition to support one hypothesis, the LR provides a theoretically founded estimate of the relative strength of its support. Despite this nice theoretical aspect, the LR accepts some practical...
The depth cues from multiple images are useful in accurate depth extraction while monocular cues from single still image are more versatile. In our paper, monocular cue which gives useful information about single frame and depth from motion using optical flow estimated from consecutive video frames are used to produce final depth maps. The machine learning approach is promising and new research direction...
Shopping of the same or similar types of products as shown in the online TV programs has been highly desired by many people, especially the youth. To meet this eminent market need, we develop a prototype system to enable effortless TV-to-Online (T2O) experience. A key component of this system is the product search that maps specific items embedded in the video into a list of online merchants. The...
The problem of distinct value estimation has many applications. Being a critical component of query optimizers in databases, it also has high commercial impact. Many distinct value estimators have been proposed, using various statistical approaches. However, characterizing the errors incurred by these estimators is an open problem: existing analytical approaches are not powerful enough, and extensive...
The development of Web applications has a crucial role as most organizations have their own corporate Web applications to meet the needs of their respective businesses. Different needs create different complexities which represent a new challenge to Web application development. In order to ensure the timely delivery of a project, software providers offering this service choose to use Open Sources...
Simulation-based acquisition (SBA) is a robust, collaborative use of modeling and simulation (M&S) technologies that are integrated across acquisition phases and programs. Our research goal is to quantitatively show the benefits from M&S in SBA. To that end, we should consider costs arisen from the use of M&S in SBA, e.g., development costs related with M&S. This paper presents a simulation...
In this paper, we introduce a formulation for a folding sum transformation and then investigate into its impact on binary classification. The proposed folding sum transformation can reduce dimension of data without a training process. The least squares estimation and a full multivariate polynomial expansion are utilized to apply the folding sum transformation for binary classification. Twelve binary...
As intelligent automation and large-scale distributed monitoring and control systems become more widespread, concerns are growing about the way these systems collect and make use of privacy-sensitive data obtained from individuals. This tutorial paper gives a systems and control perspective on the topic of privacy preserving data analysis, with a particular emphasis on the processing of dynamic data...
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