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In real robot applications, the task of designing a fuzzy logic controller is complex enough essentially because the presence of many forms of noise and uncertainties. The robot while navigating has to control many variables to get the best result at the end of the task: best smooth trajectory, the guarantee of arrive to goal, lowest time, etc. We present in this paper a novel Particle Swarm Optimization...
Distance learning has met an appearante evolution since some time ago. Thanks to the progress of Information Communication Technologies (ICT), a new approach appear in the last decades, which is a learning technique based on Television and called T-Learning. Inded, the recent technological development of Television opens a wide range of services and features. Furthermore, social inclusion in learning...
For different reasons, many viewers like to watch a summary of films in less time than it takes to play. Traditionally, video films were analyzed manually to provide its summary; however this requires an important work time. Therefore, it is a necessity to propose a tool for summarization and video analysis automatically. Automatic video summarization has to extract all important moments in which...
Face recognition is a very popular biometric solution in the literature. Several solutions are presented to meet the needs of individual's verification or identification. There are three types of face recognition approaches: local, global and hybrid. In this paper, we proposed a local approach for face recognition based on combined features selection methods like Genetic algorithm, Gramdt Shmidt algorithm,...
This article introduces an improved version of the ant-clustering approach for image segmentation. An application of breast cancer magnetic resonance breas imaging has been chosen and the improved ant-based clustering approach has been applied to see their ability and accuracy to isolate the region of interest in the MRI images. The aim of the proposed ant-based clustering is to identify target objects...
Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) algorithms have attracted the interest of researchers due to their simplicity, effectiveness and efficiency in solving real world optimization problems. Swarm-inspired optimization has recently become very popular. Both ACO and PSO are successfully applied in the Traveling Salesman Problem (TSP). Our approach consists in combining...
In this paper, we introduce a new evolutionary methodology to design fuzzy inference systems. An innovative hybrid stages of learning method and tuning method, contains Subtractive clustering, Adaptive Neuro-Fuzzy Inference System (ANFIS) and particle swarm optimization (PSO), is developed to generate evolutional fuzzy modeling systems with high accuracy. For the purpose of illustration and validation...
Recently, there has been a considerable interest on learning type-2 fuzy logic systems, essentially on how determining the footprint of uncertainties of linguistic variables. In fact, the complexity and difficulty in developing type-2 fuzzy systems can be located at the time of deciding which are the best parameters of membership functions (MFs). In real robot applications, the task of designing a...
In mobile robots, motion control systems play an important role to assume trajectory planning and obstacle avoidance. Proportional-Integral-Derivative (PID) controllers are the most popular controller used in industrial control systems including mobile robots. The PID controller is developed based on the linear control theory but it gives inconsistent performance for different condition. In order...
In this paper the investigation is placed on the hierarchic neuro-fuzzy systems as a possible solution for biped control. An hierarchic controller for biped is presented, it includes several sub-controllers and the whole structure is generated using the adaptive Neuro-fuzzy method. The proposed hierarchic system focus on the key role that the centre of mass position plays in biped robotics, the system...
Automatic grasp planning is an active field in robotic research. Its main purpose is to find the contact points between the robotic hand and an object in order to grasp it efficiently. As the robotic hand has many degrees of freedom which induce a huge number of solutions, the search for the “best” solution became an optimization problem. The search of such a solution is conducted by a grasp quality...
In this paper, we present the interest of coupling learning capability and imitation strategy on individual and population levels in the field of Multi-Robot System. Particularly, we show that in an unknown environment adding a simple imitation capability to our bio-inspired architecture leads to a positive effect in the improvement the overall performance of the whole system. Indeed, our motivations...
The goal of Brain Eyes WHEELchair Interface (BEWHEELI) project is to command and control a powered wheelchair throughout thoughts and gaze. For this purpose, a bi-modal real time collaborative system should be put in place, so it can enhance severely disabled people mobility in hostile indoor environment.
It has been both a great motivation and satisfaction to coordinate and host the 2013 International Conference on Individual and Collective Behaviors in Robotics (ICBR) - the first time in Tunisia, and in the city of Sousse.
In this paper, a tree-based encoding method is introduced to represent the Beta basis function neural network. The proposed model called Flexible Beta Basis Function Neural Tree (FBBFNT) can be created and optimized based on the predefined Beta operator sets. A hybrid learning algorithm is used to evolving FBBFNT Model: the structure is developed using the Extended Genetic Programming (EGP) and the...
This paper investigates a Naïve Bayes Style Possibilistic Classifier (NBSPC) to make decision from the categorical and subjective medical information included by the lymphog-raphy dataset of University of California Irvine (UCI). Main focus of the work is to improve the classification accuracy. NBSPC simultaneously relies on the structure of the Naïve Bayes classifier as a good classifier for categorical...
The adaptation module is a Radial Basis Function Neural Network (RBF-NN) that can be connected to the output of any recognition system and its aim is to examine the output of the writer-independent system and produce a more correct output vector close to the desired response. The proposed adaptation module is built using an incremental training named GA-AM algorithm (Growing-Adjustment Adaptation...
Scintigraphic images are often characterized with much noise and a badly contrasted resolution which makes the perception of regions of interest very difficult. The renal quantification is how to define the regions of interests whose activities informs on the status of the renal function. In this context, the current study presents an intelligent system for the segmentation of renal regions in order...
This paper addresses the problem of generating a super-resolved version of a low-resolution textual image by using Sparse Coding (SC) which suggests that image patches can be sparsely represented from a suitable dictionary. In order to enhance the learning performance and improve the reconstruction ability, we propose in this paper a multiple learned dictionaries based clustered SC approach for single...
This paper describes the Arabic Recognition Competition: Multi-font Multi-size Digitally Represented Text held in the context of the 12th International Conference on Document Analysis and Recognition (ICDAR'2013), during August 25-28, 2013, Washington DC, United States of America. This competition has used the freely available Arabic Printed Text Image (APTI) database. A first edition took place in...
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