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Text in natural scenes provides many information for peoples and presents an essential tool to interact with their environment. Therefore, recognizing text existing in camera-captured images has become an important issue for many researches in the last decades. Currently, there isn't any available dataset of Arabic script text images in the wild. Since our aim is to help the research community in...
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...
This paper first proposes a simple scheme for adapting the chemotactic step size of the Bacterial Foraging Optimization Algorithm (BFOA), and then this new adaptation and two very popular optimization techniques called Particle Swarm Optimization (PSO) and Differential Evolution (DE) are coupled in a new hybrid approach named Adaptive Chemotactic Bacterial Swarm Foraging Optimization with Differential...
This paper introduces a new hierarchical architecture for multi-objective optimization. Based on the concept of Pareto dominance, the process of implementation of the algorithm consists of two stages. First, when executing a multiobjective Particle S warm Optimization (MOPSO), a ranking operator is applied to the population in a predefined iteration to build an initial archive Using ε-dominance. Second,...
Many methods for solving optimization problems, whether direct or indirect, rely upon gradient information and therefore may converge to a local optimum. Global optimization methods like Evolutionary algorithms, overcome this problem although these techniques are computationally expensive due to slow nature of the evolutionary process. In this work, a new concept is investigated to accelerate the...
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