Adel M. Alimi

Ecole Nationale d'Ingénieurs de Sfax | ENIS · Computer Engineering and Applied Mathematics Department

Particle Swarm Optimization (PSO) system based on the distributed architecture over multiple sub-swarms is very efficient for static multi-objective optimization but has not been considered for solving dynamic multi-objective problems (DMOPs). Tracking the most effective solutions over time and ensuring good exploitation and exploration are the mai...

Hybrid cloud platforms offer an attractive solution to organizations interested in implementing integrated private and public cloud applications to meet their profitability requirements. However, this can only be achieved by utilizing available resources while speeding up execution processes. Accordingly, deploying new applications entails dedicati...

Dynamic Multi-Objective Optimization Problems (DMOPs) and Many-Objective Optimization Problems (MaOPs) are two classes of the optimization field that have potential applications in engineering. Modified Multi-Objective Evolutionary Algorithms hybrid approaches seem to be suitable to effectively deal with such problems. However, the standard Crow Se...

Representation learning impacts the performance of Machine Learning (ML) models. Feature extraction-based methods such as Auto-Encoders (AEs) are used to find new, more accurate data representations from original ones. They perform efficiently on a specific task, in terms of: (1) high accuracy, (2) large short-term memory and (3) low execution time...

Basing on the emergent evolution of web technologies and the increasing number of video consumerson the one hand, and the immense role of this multimedia data in the information diffusion in the other hand, we have thought of designing a new system which makes connection between videosand Knowledge base connected to the semantic web technologies, i...

Scientific workflows are appropriate for treating large volumes of data and leading large-scale experiments. They are time-consuming and resource-intensive applications that profit from operating within distributed platforms, like cloud computing. However, the cloud presents several challenges that must be addressed to employ workflow applications...

The beta-elliptic model (BEM) has proven a great success in several applications such as handwriting recognition and analysis, handwriting identification, the effect of age on the kinematics of hand movements , etc. With the emergence of deep learning technologies during the last years and their application in several fields, the implementation of...

The development of a Time series Forecasting System is a major concern for Artificial Intelligence researchers. Commonly, existing systems only assess temporal features and analyze the behavior of the data over time, thus, resulting in uncertain forecasting accuracy. Although many forecasting systems were proposed in the literature; they have not y...

This paper first reviews heuristic-based and bio-inspired contributions in inverse kinematics. A new inverse kinematics solver is then proposed based on beta distributed Salp Swarm Algorithm called β-SSA. The proposed algorithm is an alternative of the SSA algorithm where leading salps are distributed based on the beta function, enabling a better c...

This paper focuses on the face detection problem of three popular animal categories that need control such as horses, cats and dogs. Existing detectors are generally based on Convolutional Neural Networks (CNNs) as backbones. CNNs are strong and fascinating classification tools but present some weak points such as the big number of layers and param...

p>The detection and recognition of road traffic signs and panel guides content has become challenging in recent years. Few studies have been made to solve these two issues at the same time especially in Arabic language. Additionally, the limited number of datasets for traffic signs and panel guide content makes the investigation more interesting. I...

p>The detection and recognition of road traffic signs and panel guides content has become challenging in recent years. Few studies have been made to solve these two issues at the same time especially in Arabic language. Additionally, the limited number of datasets for traffic signs and panel guide content makes the investigation more interesting. I...

Since the last years and until now, technology has made fast progress for many industries, in particularly, garment industry which aims to follow consumer desires and demands. One of these demands is to fit clothes before purchasing them on-line. Therefore, many research works have been focused on how to develop an intelligent apparel industry to e...

Online signals are rich in dynamic features such as trajectory chronology, velocity, pressure and pen up/down movements. Their offline counterparts consist of a set of pixels. Thus, online handwriting recognition accuracy is generally better than offline. In this paper, we propose an original framework for recovering temporal order and pen velocity...

This work is part of an innovative e-learning project allowing the development of an advanced digital educational tool that provides feedback during the process of learning handwriting for young school children (three to eight years old). In this paper, we describe a new method for children handwriting quality analysis. It automatically detects mis...

p>Fake account detection is a topical issue when many Online Social Networks (OSNs) encounter problems caused by a growing number of unethical online social activities. This study presents a new Quantum Beta-Distributed Multi-Objective Particle Swarm Optimization (QBD-MOPSO) system to detect fake accounts on Twitter. The proposed system aims to min...

p>Fake account detection is a topical issue when many Online Social Networks (OSNs) encounter problems caused by a growing number of unethical online social activities. This study presents a new Quantum Beta-Distributed Multi-Objective Particle Swarm Optimization (QBD-MOPSO) system to detect fake accounts on Twitter. The proposed system aims to min...

Human activity recognition (HAR) is a highly prized application in the pattern recognition and the computer vision fields. Up till now, deep neural networks have acquired big attention in computer studies and image processing fields, and have generated significant results. In this paper, we propose a deep temporal residual system for daily living a...

The active modality of handwriting is broadly related to signature verification in the context of biometric user authentication systems. Signature verification aims to verify a questioned signature as being genuine or forged compared to some previously provided signatures from the claimed person. By doing so, we may be able to verify a person’s ide...

Providing labeled Arabic text images dataset for scene text detection is inherently difficult and costly at the same time. Consequently, only few small datasets are available for this task. Previous work has only focused on the data augmentation technique of small datasets; however, the images generated with these techniques cannot reproduce the co...

As an increasingly larger number of users partake in Facebook, the images shared and posted by user in Facebook provide a richer background to build a more accurate recommendation system. In this paper, we propose an Intelligent Recommendation System for Travelers’ Preferences (IRSTP) based on the conceptualization of the travel user’s destination...

Deep convolutional neural networks (Deep CNN) have achieved hopeful performance for single image super-resolution. In particular, the Deep CNN skip Connection and Network in Network (DCSCN) architecture has been successfully applied to natural images super-resolution. In this work we propose an approach called SDT-DCSCN that jointly performs super-...

Our work presents a virtual fitting system called Dress-up aiming to treat the task of human appearance transfer across images while preserving texture details and structural coherence of the generated outfit.

Our work presents a virtual fitting system called Dress-up aiming to treat the task of human appearance transfer across images while preserving texture details and structural coherence of the generated outfit.

Particle swarm optimization system based on the distributed architecture over multiple sub-swarms has shown its efficiency for static optimization and has not been studied to solve dynamic multi-objective problems (DMOPs). When solving DMOP, tracking the best solutions over time and ensuring good exploitation and exploration are the main challengin...

Given the competition and rapidly-evolving market associated challenges, companies need to be innovative and agile, particularly regarding the customers dedicated web applications. Nowadays, hybrid cloud stands as an attractive solution for organizations that tend to use a combination of private and public cloud implementations, following their app...

A newly introduced method called Taylor-based Optimized Recursive Extended Exponential Smoothed Neural Networks Forecasting method is applied and extended in this study to forecast numerical values. Unlike traditional forecasting techniques which forecast only future values, our proposed method provides a new extension to correct the predicted valu...

A newly introduced method called Taylor-based Optimized Recursive Extended Exponential Smoothed Neural Networks Forecasting method is applied and extended in this study to forecast numerical values. Unlike traditional forecasting techniques which forecast only future values, our proposed method provides a new extension to correct the predicted valu...

div>- A novel approach is presented to reduced annotation based on Deep Active Learning for Arabic text detection in Natural Scene Images. - A new Arabic text images dataset (7k images) using the Google Street View service named TSVD. - A new semi-automatic method for generating natural scene text images from the streets. - Training samples is r...

div>- A novel approach is presented to reduced annotation based on Deep Active Learning for Arabic text detection in Natural Scene Images. - A new Arabic text images dataset (7k images) using the Google Street View service named TSVD. - A new semi-automatic method for generating natural scene text images from the streets. - Training samples is r...

p>Multifactorial Optimization (MFO) and Evolutionary Transfer Optimization (ETO) are new optimization challenging paradigms for which the multi-Objective Particle Swarm Optimization system (MOPSO) may be interesting despite limitations. MOPSO has been widely used in static/dynamic multi-objective optimization problems, while its potentials for mult...

p>Multifactorial Optimization (MFO) and Evolutionary Transfer Optimization (ETO) are new optimization challenging paradigms for which the multi-Objective Particle Swarm Optimization system (MOPSO) may be interesting despite limitations. MOPSO has been widely used in static/dynamic multi-objective optimization problems, while its potentials for mult...

Particle swarm optimization system based on the distributed architecture has shown its efficiency for static optimization and has not been studied to solve dynamic multiobjective problems (DMOPs). When solving DMOP, tracking the best solutions over time and ensuring good exploitation and exploration are the main challenging tasks. This study propos...

Particle swarm optimization system based on the distributed architecture has shown its efficiency for static optimization and has not been studied to solve dynamic multiobjective problems (DMOPs). When solving DMOP, tracking the best solutions over time and ensuring good exploitation and exploration are the main challenging tasks. This study propos...

div>The Ultra-Large-Scale Software (ULSS) systems development challenges today’s software management and development approaches. Northrop et al. (2006) revealed three broad areas of challenges [1]. To deal with those challenges, they propose an interdisciplinary portfolio of research. In particular, we address the design and evolution challenge by...

div>Epilepsy affect almost 1% of the worldwide population. An early diagnosis of seizure types is a patient-dependent process which is crucial for the treatment selection process. The selection of the proper treatment relies on the correct identification of seizures type. As such, identifying the seizure type has the biggest immediate influence on...

div>Epilepsy affect almost 1% of the worldwide population. An early diagnosis of seizure types is a patient-dependent process which is crucial for the treatment selection process. The selection of the proper treatment relies on the correct identification of seizures type. As such, identifying the seizure type has the biggest immediate influence on...

Online signals are rich in dynamic features such as trajectory chronology, velocity, pressure and pen up/down movements. Their offline counterparts consist of a set of pixels. Thus, online handwriting recognition accuracy is generally better than offline. In this paper, we propose an original framework for recovering temporal order and pen velocity...

Recognizing text within camera-captured images has been a very significant research topic for the last decades. In this paper, we intend to recognize Latin/Arabic text in natural scenes. For this reason, we present a comparative study between handcrafted and hybrid features. To acquire handcrafted features, we employ a standard bag of features (BoF...

This work is part of an innovative e-learning project allowing the development of an advanced digital educational tool that provides feedback during the process of learning handwriting for young school children (three to eight years old). In this paper, we describe a new method for children handwriting quality analysis. It automatically detects mis...

Horses and breeders need to be safe on the farm and the riding club. On account of the great value of the horse, the breeder needs to protect it from theft and disease. In this context, it is important to detect and to recognize the identity of each horse for security reasons. In fact, this paper proposes a Smart Riding Club Biometric System (SRCBS...

Horses and breeders need to be safe on the farm and the riding club. On account of the great value of the horse, the breeder needs to protect it from theft and disease. In this context, it is important to detect and to recognize the identity of each horse for security reasons. In fact, this paper proposes a Smart Riding Club Biometric System (SRCBS...

Deep data analysis for latent information prediction has been an important research area. Many of the existing solutions have used the textual data and have obtained an accurate results for predicting users' interests and other latent attributes. However, little attention has been paid to visual data that is becoming increasingly popular in recent...

Deep data analysis for latent information prediction has been an important research area. Many of the existing solutions have used the textual data and have obtained an accurate results for predicting users' interests and other latent attributes. However, little attention has been paid to visual data that is becoming increasingly popular in recent...

This paper investigates whether age, gender, and degree of familiarity with writing have an influence on the Beta-elliptic model errors during hand-drawing on a graphical tablet. A database of elliptical hand drawing movements was built within a sample of 99 participants aged between 19 and 85 years. Using the Beta-elliptic model, the velocity prof...

p>Dynamic multi-objective optimization problems (DMOPs) and Many-Objective Optimization Problems (MaOPs) are two classes of the optimization filed which have potential applications in engineering. Modified Multi-Objective Evolutionary Algorithms hybrid approaches seem to be suitable to effectively deal with such problems. However, the Crow Search A...

p>Dynamic multi-objective optimization problems (DMOPs) and Many-Objective Optimization Problems (MaOPs) are two classes of the optimization filed which have potential applications in engineering. Modified Multi-Objective Evolutionary Algorithms hybrid approaches seem to be suitable to effectively deal with such problems. However, the Crow Search A...

p>Dynamic multi-objective optimization problems (DMOPs) and Many-Objective Optimization Problems (MaOPs) are two classes of the optimization filed which have potential applications in engineering. Modified Multi-Objective Evolutionary Algorithms hybrid approaches seem to be suitable to effectively deal with such problems. However, the Crow Search A...

This paper presents the Online Arabic words recognition competition (OAWRC 2021) held at ASAR 2021 workshop in conjuction with ICDAR 2021. This competition uses the ADAB database, which is a database of Arabic handwritten words. Three groups with four systems are participating in the competition this year. A brief description of participating syste...

This paper describes the online Arabic writer identification competition held at ICDAR 2021 Workshop on Arabic and derived Script Analysis and Recognition (ASAR 2021, 4th edition). This first competition of online writer identification uses the ADAB database with online Arabic handwritten words which represent the Tunisian town names. Four systems...

The online Arabic handwriting recognition task always presents a challenge due to the existence of some complexity and variability of its writing style. In this paper, we describe an online Arabic handwritten Character recognition competition (ACRC) held at ASAR 2021. The aim is to evaluate the limits of Arabic character recognition systems on coll...

The lack of large training data in the context of deep learning applications is a serious issue investigated by many studies that deal with the current challenge. In this paper, we introduce new data augmentation methods that generate more shape and dynamic variations to improve the performance of recognition systems using small datasets. Four data...

Stroke reconstruction from offline handwriting is an important research field. This article presents Online Signal Restoration (OSR) using Arabic Handwriting Dhad Dataset competition organized at ASAR 2021. The goal of this competition is to collect different systems and compare recent advances in online handwriting recovery. This competition has a...

p>Our work aims to conduct a comprehensive literature review of deep learning methods applied in the fashion industry and, especially, the image-based virtual fitting task by citing research works published in the last years. We have summarized their challenges, their main frameworks, the popular benchmark datasets, and the different evaluation met...

Anxiety affects human capabilities and behavior as much as it affects productivity and quality of life. It is considered to be the main cause of depression and suicide. Anxious states are detectable by specialists by virtue of their acquired cognition and skills. There is a need for non-invasive reliable techniques that performs the complex task of...

div>The Ultra-Large-Scale Software (ULSS) systems development challenges today’s software management and development approaches. Northrop et al. (2006) revealed three broad areas of challenges [1]. To deal with those challenges, they propose an interdisciplinary portfolio of research. In particular, we address the design and evolution challenge by...

div>An innovative e-learning project is presented in this paper, which is a mobile workbook that teaches handwriting at school. This mobile application proposes a new qualitative and quantitative analysis process of online cursive handwriting. It gives a real-time feedback, detects mistakes and helps teachers evaluate children’s writing skills. The...

div>An innovative e-learning project is presented in this paper, which is a mobile workbook that teaches handwriting at school. This mobile application proposes a new qualitative and quantitative analysis process of online cursive handwriting. It gives a real-time feedback, detects mistakes and helps teachers evaluate children’s writing skills. The...

In this paper a new technique is integrated to Multi-Objective Particle Swarm Optimization (MOPSO) algorithm, named Pareto Neighborhood (PN) topology, to produce MOPSO-PN algorithm. This technique involves iteratively selecting a set of best solutions from the Pareto-Optimal-Fronts and trying to explore them in order to find better clustering resul...

In this paper a new technique is integrated to Multi-Objective Particle Swarm Optimization (MOPSO) algorithm, named Pareto Neighborhood (PN) topology, to produce MOPSO-PN algorithm. This technique involves iteratively selecting a set of best solutions from the Pareto-Optimal-Fronts and trying to explore them in order to find better clustering resul...

In this paper a new technique is integrated to Multi-Objective Particle Swarm Optimization (MOPSO) algorithm, named Pareto Neighborhood (PN) topology, to produce MOPSO-PN algorithm. This technique involves iteratively selecting a set of best solutions from the Pareto-Optimal-Fronts and trying to explore them in order to find better clustering resul...