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Human interact with natural language. Words are uncertain, vague and imprecise. Besides, words mean different things to different people. So, the use of numerical model to represent words is a difficult task. In this paper, we propose to give a new review of the most used computing with words methods especially encoding ones. Many approaches were used for computing with words. Some of these methods...
This paper presents a new video surveillance system called KVSS using background based on Type-2 Fuzzy Gaussian Mixture Models (T2 FGMMs). These techniques are used for resolving some limitations on Gaussian Mixture Models (GMMs) techniques on critical situations like moved camera jitter, illumination changes and objects being introduced or removed from the scene. In this context, we introduce descriptions...
Recent advances in information and communication technologies offer wide variety methods of exchange over the network. The telepresence robot is an example of these techonol-gies. This paper presents our approach to build an intelligent telepresence robot called “REGIMTEL” by using commercialized Android tablet PC. REGIMTEL can be used as an agent to supervise and to communicate with children or elders...
This work is located in the domain of the Knowledge Discovery from Data (KDD). The purpose of the KDD is the extraction of knowledge or of a knowledge starting from great number of data which evolve in a dynamic way. In this work we propose an approach for the temporal KDD. The Bayesian Network (BN) is one of the techniques used in KDD. Our objective comes back to fix the best algorithm of incremental...
In this report, we propose to give a review of the most used clustering methods in the literature. First, we give an introduction about clustering methods, how they work and their main challenges. Second, we present the clustering methods with some comparisons including mainly the classical partitioning clustering methods like well-known k-means algorithms, Gaussian Mixture Modals and their variants,...
Biometrics-based hand authentication is among the most popular biometrics used to automatically characterize a person especially in forensic applications. Hand recognition systems are able to confirm or deny the identity of a claimed person because they do not cause anxiety for the users. However, different individuals may have almost similar hands. Therefore, the performance of the hand verification...
In this paper, we propose a modified Hybrid Naïve Possibilistic Classifier (HNPC) for heart disease detection from the heterogeneous data (numerical and categorical) of the Cleveland dataset. The proposed classifier is based on a different pattern with regard to our former HNPC which have been recently proposed to deal with the same problem. As HNPC, the modified classifier separates data into two...
Face Recognition is among the most widely studied problems in computer vision and Pattern Recognition. Face has many advantages like permanence, accessibility and universality. It is still now not solved in literature. Several approaches are proposed to overcome with problems including; changing posed, emotional states, and illumination variation, etc. Geometric approaches which used as example distance...
This paper discuss the oscillations of high-Order type recurrent delayed neural networks. Various creteria are used to prove the existence and uniqueness of pseudo almost periodic solution in a suitable convex domain. Our method is based on constructing suitable Lyapunov functionals and the well-known Banach contraction mapping principle. Banach fixed point, pseudo almost-periodic functions, high...
In this paper, the universal approximation propriety is proved for the Flexible Beta Basis Function Neural Tree (FBBFNT) model. This model is a tree-encoding method for designing Beta basis function neural network. The performance of FBBFNT is evaluated for benchmark problems drawn from time series approximation area and is compared with other methods in the literature.
This paper provides an overview on a new evolutionary approach based on an intelligent multi-agent architecture to design Beta fuzzy systems (BFSs). The Methodology consists of two processes, a learning process using a clustering technique for the automated design of an initial Beta fuzzy system, and a multi-agent tuning process based on Particle Swarm Optimization algorithm to deal with the optimization...
Multi-Agent System (MAS) is a very active field that ensures global coherence between agents' interactions in a distributed way and implicit global control. Under the awareness of its power, the application of MAS was no more limited to very specific problems, but to almost application area: optimization, neural network, robotics, fuzzy system, etc. In the other side, a complex system of Artificial...
Usually, road networks are characterized by their great dynamics including different entities in interactions. This leads to more complex road traffic management. This paper proposes an adaptive multiagent system based on the ant colony behavior and the hierarchical fuzzy model. This system allows adjusting efficiently the road traffic according to the real-time changes in road networks by the integration...
In this paper, we present an integrated system able to localize multi-oriented handwritten annotations in scanned documents. Unlike previous single methods which limit colors or types of annotations to be extracted, the proposed method attempts to extract annotations by fusing three feature extraction techniques based on internal and external shape analysis. Our method consists of two processes: 1)...
Face recognition is very used in biometric market for many reasons. Face can be detected at distance without user's implication in enrollment process. Face recognition systems are still expanded in video surveillance areas to control access. This paper presents an experimental study on some proposed face recognition approaches by building systems with different techniques for features extraction and...
Aerial Video-Surveillance systems are being more and more used in security applications. The analysis and detection of abnormal behaviours in a aerial sequence has progressively drawn the attention in the field of public area security, since it allows filtering out a large number of useless information, which guarantees the high efficiency in the security protection, and save a lot of human and material...
We propose in this paper an emotional recognition system based on physiological signals. We adopt the seven basic emotions that are: neutrality, joy, sadness, fear, anger, disgust and surprise. An experiment has been conducted to verify the feasibility of the proposed system. This experience has allowed us to acquire EEG signals and to create an emotional database. For this, we have used the Emotiv...
This paper discusses the use of intelligent technology to solve the problem of grasp planning known as a difficult problem. The scope aims to find points of contact between a five-fingered hand and an object. In this paper, we applied a new hierarchical approach for distributed Multi-Objective Particles Swarms Optimization, based on dynamic subdivision of the population using Pareto fronts (pbMOPSO)...
This paper investigates a Hybrid Naïve Possibilistic Classifier (HNPC) to detect the presence of heart disease from the heterogeneous data (numerical and categorical) of the Cleveland dataset. The proposed classifier stands for the hybridization of two versions of Naïve Possibilistic Classifier (NPC) which have been recently applied on numerical and categorical data, respectively. To estimate possibility...
Chemical compounds have a biological activity on animal genes; Mutagenicity and Carcinogenicity are examples of this activity. Both activities are similar except that mutagen compounds induce a heritable change in cells, while carcinogen compounds induce an unregulated growth process in cells. The relation between Mutagenicity and Carcinogenicity is not proved quantitatively yet. In this article,...
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