Abdennour Boulesnane

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• Doctor of Philosophy
• Professor (Associate) at University of Constantine 3

Sign language serves as a dynamic means of communication, facilitating expression and emotional connection among individuals who are deaf or hard of hearing and the broader community. However, persistent communication barriers impact various sectors, including healthcare and education. Sign Language Recognition (SLR) systems bridge this gap by leve...

This paper presents ASLAD-190K, a comprehensive dataset comprising 190,000 annotated RGB images representing 32 distinct Arabic Sign Language letters and gestures. Designed to support machine learning and computer vision research, ASLAD-190K offers a diverse range of images collected under varying lighting conditions, distances, and backgrounds to...

Evolutionary Computation (EC) has emerged as a powerful field of Artificial Intelligence, inspired by nature’s mechanisms of gradual development. However, EC approaches often face challenges such as stagnation, diversity loss, computational complexity, population initialization, and premature convergence. To overcome these limitations, researchers...

In light of the global crisis like COVID-19, many people are afraid to leave the house and visit the doctor for fear of these epidemics. On the other side, the amazing development of artificial intelligence has led to chatbots' emergence and use in several fields. Therefore, in this paper, we propose to build an automated chatbot system that intera...

The emergence of LLMs, like ChatGPT and Gemini, has marked the modern era of artificial intelligence applications characterized by high-impact applications generating text, images, and videos. However, these models usually ensue with one critical challenge called hallucination: confident presentation of inaccurate or fabricated information. This pr...

Medical imaging has significantly revolutionized medical diagnostics and treatment planning, progressing from early X-ray usage to sophisticated methods like MRIs, CT scans, and ultrasounds. This paper investigates the use of deep learning for medical image captioning, with a particular focus on uterine ultrasound images. These images are vital in...

Language is the fundamental means of communication in our daily lives, encompassing various aspects of individual behavior. However, for the deaf community, the absence of participation in the language communication system due to hearing impairment results in a significant disability that leads to isolation. This communication barrier has detriment...

Evolutionary Computation (EC) has emerged as a powerful field of Artificial Intelligence, inspired by nature's mechanisms of gradual development. However, EC approaches often face challenges such as stagnation, diversity loss, computational complexity, population initialization, and premature convergence. To overcome these limitations, researchers...

The task of extracting sentiment from text has been widely studied in the field of natural language processing. However, little work has been conducted specifically on the Arabic language with the Algerian dialect. In this research, we aim to make a significant contribution to the field of sentiment analysis on the Algerian dialect by creating a cu...

The recent large outbreak of infectious diseases, such as influenza-like illnesses and COVID-19, has resulted in a flood of health-related posts on the Internet in general and on social media in particular, in a wide range of languages and dialects around the world. The obvious relationship between the number of infectious disease cases and the num...

Solving dynamic optimization problems is more challenging than static ones. When a change in the objective landscape occurs, the search process may not be powerful enough to track new optima. For population based algorithms this is referred to as diversity loss problem. Furthermore, the memory of old optima becomes outdated and if not correctly dea...

The first international seminar on pollution, health, environment and bio-monitoring, will be organized by the Department of Science and Nature and Life of the University of August 20, 1955-Skikda online (web meeting); this is in projection of the effect of Covid-19 pandemic. Public health, the appearance or disappearance of certain living species,...

Because of the great evolution of communication technologies, the subject of information security has become a sensitive topic that must be given great importance in order to protect confidential information. Steganography is one of the effective ways to improve security and information protection while transferring data over the Internet. It consi...

In this work, we propose to use for the first time in the literature, the position of points in dotted Arabic letters combining with other Arabic text features to create a new steganography technique. Based on this idea, we introduce new secret bit patterns that could allow us to hide three bits of secret information into a cover object instead of...

Motivated by the fact that the problem of online feature selection is a dynamic problem whose dimension (feature) changes over time, we propose a hybridization between the dynamic optimization algorithms and the Online Streaming Feature Selection algorithm (OSFS) (https://github.com/kuiy/LOFS), whose objective is to find a subset of optimal attribu...

Many real-world applications require optimization in dynamic environments where the challenge is to find optima of a time-dependent objective function while tracking them over time. Many evolutionary approaches have been developed to solve Dynamic Optimization Problems (DOPs). However, there is still a need for more efficient methods. Recently, a n...

Feature selection is a key issue in machine learning and data mining. A great deal of effort has been devoted to static feature selection. However, with the assumption that features occur over time, methods developed so far are difficult to use if not applicable. Therefore, there is a need to design new methods to deal with streaming feature select...

This thesis addresses issues related to optimization in dynamic environments where the matter is not only being able to identify optima in ever changing objective functions landscapes but also to track them over time at each change of the landscape. Many real world problems are of this nature and require the development of effective approaches to s...

Modèle et Approches pour l’Optimisation Multi-Populations et Multi-Régions dans les Environnements Dynamiques : Application à la sélection d’attributs en ligne

Dynamic optimization holds promise to solve real world problems that require adaptation to dynamic environments. The challenge is to track optima in an ever changing landscape. This paper describes a new computational intelligence approach to dynamic optimization termed as wind driven dynamic optimization (WD2O). Basically, it relies on an enhanced...

Metaheuristics have been proposed as an alternative to mathematical optimization methods to address non convex problems involving large search spaces. Within this context a new promising metaheuristic inspired from earth atmosphere phenomena and termed as Wind Driven Optimization (WDO) has been developed by Bayraktar. WDO has been successfully appl...

The performance of the proposed modified WDO has been assessed using several benchmarks in numerical optimization. The obtained results show that the modified WDO outperforms the original WDO in most test problems from both accuracy and robustness.

This paper describes a new approach to deal with dynamic optimization that uses a multi-population. Its main features include the use of a modified wind driven optimization algorithm that aims to foster impact of pressure on velocities of particles. Moreover, a concept of multi-region inspired from meteorology has been introduced along with a new c...

In this report, we will present an example of the use of the Atom3 tool to develop an NFA (Non-Deterministic) or DFA (Deterministic) finite-state automaton and also a transformation from an NFA to a DFA.