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Automatic Target Recognition (ATR) aims at detecting the presence and at recognizing the typology and the orientation of targets within a scenario, by using an unsupervised approach. In Syntethic Aperture Radar imaging this turns to be a difficult task due to the specific characteristics of clutter and background noise. Within this manuscript a new two-steps ATR algorithm based on Kolmogorov-Smirnov...
The major objective of mobility management is to achieve efficient contents transfer for mobile nodes. Content Centric Networking (CCN), as a content-oriented architecture, is designed for efficient content delivery which can easily provide mobility management based on content caching. Caching schemes of CCN deeply influences the content acquisition efficiency and whole network performance. However,...
Many people undergo from the stress in their everyday life. Due to there close relationship between the stress, mental health and psychological aspect. Stress management using EEG data is very challenging task. In this paper, classification of EEG data is done by using statistical techniques like, mean, standard deviation, variance and correlation. This algorithm got the 0.0056 correlation which is...
Purpose of this paper is to present a computerized way to evaluate CTG recordings, and more specifically use of feature clustering for the classification process. We used a database which contained 552 records and 20 features. Matlab (version R2012a) was used for the experiments. First we performed a reduction of the number of features used in order to end up only with the most useful ones. That set...
In this paper, a simple and effective multibiometric technique for subject recognition using multiple lead electrocardiogram (ECG) signals is presented. The proposed technique significantly improves the recognition performance of a biometric system by using multiple sources available in the same modality group. A total of 30 subjects with 12 lead ECG measurements obtained from PTB Diagnostic ECG database...
Researchers in the database community have aroused great interest in handling high dimensional data sets for the past decades. Today's business captures inundate sets of data which includes digital documents, web pages-customer databases, hyper-spectral imagery, social networks, gene arrays, proteomics data, neurobiological signals, high dimensional dynamical systems, sensor networks, financial transactions...
With the rapid development of database technique, categorizing datasets becomes very important for discovering information. Decision tree classification provides a rapid and effective method of categorizing datasets. Although many algorithmic methods exist for optimizing decision tree structure, these can be vulnerable to changes in the training dataset. In this paper, an evolutionary method is presented,...
In the paper, put forward classification and discrimination based on rough sets-partial least squares-discriminant analysis (RS-PLS-DA). The method was proved to be feasible and effective after tested with a complication of diabetes database.
Query relaxation refers to the process of reducing the number of constraints on a query if it returns no result when searching a database. This is an important process to enable extraction of an appropriate number of query results because queries that are too strictly constrained may return no result, whereas queries that are too loosely constrained may return too many results. This paper proposes...
This paper presents a novel approach for off-line text-independent Arabic writer identification. The approach operates in four steps: 1) handwritten text is segmented into strokes after an image thinning step; 2)length, height/width ratio and curvature stroke features are extracted; 3) five feature vectors are computed: stroke length/ratio probability distribution function (PDF), stroke length/ratio...
With the full use of syndrome differentiation theory and making the best of the treatment of medicated diet, the dietetic therapy of traditional Chinese medicine is devoted to harmonize the Yin, Yang, Qi, blood within the human body, to improve human body's health effectively. In this paper, we proposed an improved information gain method based on information gain method and TF-IDF method to express...
To achieve a good performance for shape classification, it requires both shape representation and classifier. In this paper, the so-called Eigen Barycenter Contour (EBcC) and Fisher Barycenter Contour (FBcC) techniques are presented for 2D shape classification. The representation utilizes the area of triangles at different scale level of Barycenter Contour (BcC). However, it is not invariant to starting...
This paper describes pitch tracking techniques, which combine voiced/unvoiced classification and pitch estimation based on cepstral analysis, time autocorrelation, spectro-temporal autocorrelation (STA) and average magnitude difference function (AMDF). Pre- and post processing techniques improving performance of pitch detection algorithms (PDAs) are also presented. PDAs have been evaluated by telephone...
Recent advancements in computing and digital signal processing technologies have made automated identification of people based on their biological, physiological, or behavioral traits a feasible approach for access control. The wide variety of available technologies has also increased the number of traits and features that can be collected and used to more accurately identify people. Systems that...
To design geometrically motivated approaches for classifying the high-dimensional data, we propose to learn a discriminant subspace using Correlation Embedding Analysis (CEA). This novel algorithm enhances its discriminant power by incorporating both correlational graph embedding and Fisher criterion. In a geometric interpretation, it projects the high- dimensional data onto a hypersphere and preserves...
In this work an innovative system biometric of writerspsila identification based in technical expert calligraphic and graphology on the handwritten script is presented. It has been developed working in off-line mode on a Spanish words image database, formed by 29 different individuals. All the extractions of characteristics carried out on the images and that they have been used for the identification,...
With rapid development of Internet information, It is quite an important project for data mining that how to classify these large amounts of texts. In this paper, we propose an improved text classify cluster algorithm, while calculating similarity, we synthetically consider the relationship between keywords and eigenvector representation on base of term frequency statistics, thereby it lessens sensitivity...
In this paper, a new concept of up-to-date patterns is proposed, which is a hybrid of the association rules and temporal mining. An up-to-date pattern is composed of an item set and its up-to-date lifetime, in which the user-defined minimum support threshold must be satisfied. The proposed approach can mine more useful large itemsets than the conventional ones which discover large itemsets valid only...
This paper proposes a technique for automatically recognising shoeprint images for use in forensic science. The method uses the Fourier-Mellin transform to produce translation, rotation and scale invariant features. A two dimensional correlation is employed as the similarity metric for the classification process. Experiments were conducted on a database of 500 different shoeprint images representing...
In this paper, we address the pair-activity classification problem, which explores the relationship between two active objects based on their motion information. Our contributions are three-fold. First, we design a set of features, e.g., causality ratio and feedback ratio based on the Granger Causality Test (GCT), for describing the pair-activities encoded as trajectory pairs. These features along...
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