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In recent years, growing attention has been paid to recognizing text in natural scenes images. Scene Character recognition (SCR) is an important step in automatizing the process of reading text in natural scenes.
In this paper, a multi-agent system is introduced to parallelize the Flexible Beta Basis Function Neural Network (FBBFNT)’ training as a response to the time cost challenge. Different agents are formed; a Structure Agent is designed for the FBBFNT structure optimization and a variable set of Parameter Agents is used for the FBBFNT parameter optimization. The main objectives of the FBBFNT learning...
The problems of our life can have many solutions (alternatives) and can be resolved based on different criteria (attributes). Thus, different weight methods exist on literature to accord an importance for each criteria. In this work TOPSIS, multi-criteria decision making (MCDM) method is presented using intuitionistic fuzzy data set with different techniques of weight proposed in literature. Therefore,...
Nowadays, Internet users act deeply on Internet content through Web 2.0. They are increasingly directing Web 2.0 and so political, economic, financial and social environments all over the world and particularly in Tunisia that is suffering from environment unsteadiness since the political revolution in 2011. Thus, Web 2.0 monitoring, that requires the use of natural language processing tools, is becoming...
Text detection in natural scenes holds great importance in the field of research and still remains a challenge because of size, various fonts, line orientation, different illumination conditions, weak character and complex background in image. The contribution of the proposed method is filtering out complex backgrounds by utilizing two masks filtering based on text confidence map in the first step...
Lying is among the most common wrong human acts that merits spending time thinking about it. The lie detection is until now posing a problem in recent research which aims to develop a non-contact application in order to estimate physiological changes. In this paper, we have proposed a preliminary investigation on which relevant acoustic parameter can be useful to classify lie or truth from speech...
We introduce a new method Near-Fuzzy set for analysis image. Indeed, near sets are considered a generalization of the rough sets theory. A set X is close to another set Y insofar as the description of at least one of the object of X corresponds to the description of least one of objects of Y. Find the tolerance classes with objects of the same description is a major problem. Maximal Clique Enumeration...
This paper provides a new method for arranging data sets into clusters. The proposed model, called FlyAntClass, starts from the ants collective sorting behavior and overwrites it with additional behaviors inspired from birds and spiders: in this context, birds' moving behavior is used to control next relative positions for a moving ant; and spiders' homing behavior is provided to manage movements...
Feature selection is a very important technique in machine learning and pattern classification. Feature selection studies using batch learning methods are inefficient when handling big data in real world, especially when data arrives sequentially. Online Feature Selection is a new paradigm which is more efficient than batch feature selection methods but it still very challenging in large-scale ultra-high...
With the evolution of cloud computing technology, companies develop their private cloud to deploy and run applications. A company can also combine public and private cloud services through the deployment of a hybrid cloud. Thus, if the company needs exceed the capacity of the private cloud, they can migrate to the public cloud. The deployment of new applications consists to choose the placement of...
In this paper, we prove the existence and the global exponential stability of the unique weighted pseudo almost-periodic solution of shunting inhibitory cellular neural networks with mixed time-varying delays comprising different discrete and distributed time delays. Some sufficient conditions are given for the existence and the global exponential stability of the weighted pseudo almost-periodic solution...
Palmprint identification is a popular biometric technology used for personal characterization. Traditional palmprint recognition methods are mostly based on acquisition devices with contact, and this, may affect their user friendliness. In this paper, a toucheless palmprint identification method based on Scale Invariant Feature Transform (SIFT) descriptors and sparse representation method is proposed,...
This paper describes a method for extracting relevant tokens of entity from semi-structured administrative documents. This method is used for mislabeling correction by employing the entity tokens physically close in a document. Firstly, the entities are labeled. Secondly, each entity is modeled by a tokens structure graph in which the nodes represent the tokens and the arcs represent the distances...
Optimization process occurs in many aspects and areas of everyday life. However, the big use of the internet in recent years caused a complex management of large quantities of data that are stored in many different data sources and optimization attend the domain of big data to optimize multi and dynamic data that stored in a complex dataset including all types of transactions in the data sources....
Online Feature Selection (OFS) is an important technique in pattern recognition and machine learning. Our challenge is how to enhance the classification performance in real contexts where the large-scale training data arrive sequentially with a big number of features. The major problem is how to choose the best accurate and efficient state-of-the art OFS method that can select the relevant features...
The automated evolutionary design of an optimal hierarchical fuzzy system combined with the use of Interval Type-2 Fuzzy Systems and the Beta basis function is considered in this study. The resulted proposed system is named the Hierarchical interval Type-2 Beta Fuzzy System (HT2BFS). For the learning process, two main optimizations steps are considered. The first one executes the structure learning...
AS-PSO-2Opt is a new enhancement of the AS-PSO method. In the classical AS-PSO, the Ant heuristic is used to optimize the tour length of a Traveling Salesman Problem, TSP, and PSO is applied to optimize three parameters of ACO, (α, β, ρ). The AS-PSO-2Opt consider a post processing resuming path redundancy, helping to improve local solutions and to decrease the probability of falling in local minimum...
This work is interested to show the importance of possibility theory in multi-criteria decision making (MCDM). Thus, we apply some intuitionistic fuzzy possibility measures from literature to the MCDM method using intuitionistic fuzzy sets (IFSs). These measures are applied to a decision matrix after being transformed with intuitionistic aggregation operators. The results are compared to previous...
Information fusion is a research domain that strives to establish theories that exploit and analyze the data retrieved from multiple sources. Generally, these fusion theories try to combine these data for a classification task and to make the decision efficiently. The possibility theory is one of the most known in the information fusion domain. So, the possibility distribution estimation step represents...
In this paper we proposed a writer adaptation system based on an adaptation module that is a plug-in for any writer-independent handwriting recognition systems. The adaptation module is a radial basis function neural network (RBF-NN) that is built using an incremental learning algorithm named GALTM-AM algorithm (Growing-Adjustment with Long-Term Memory). GALTM-AM train a new given data with some LTM...
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