Adel M. Alimi

• Eng, PhD, HdR
• Professor (Full) at National Engineering School of Sfax

Comorbidity, the simultaneous existence of multiple medical conditions in a patient, is a major challenge in healthcare. Comorbidity is highly threatening for healthcare systems, which requires innovative solutions over traditional methods. The medical field is challenged by accurately diagnosing these intertwined diseases of coexisting ailments an...

With the growth of the Internet, medical documents have become widely used by healthcare professionals. Secure transmission and management of medical images are essential to enable collaboration while protecting sensitive patient information. This study analyzes various methods for safe medical data sharing, highlighting their advantages and limita...

Facial Expression Recognition (FER) is currently a very active field of research. It involves a computer’s capability to recognize and interpret human emotional expressions, which change with an individual’s internal emotional state. Several researchers have been working on this topic, using classical methods or Neural Network (NN) approaches. The...

In the domain of handwritten character recognition, inpainting occluded offline characters is essential. Relying on the remarkable achievements of transformers in various tasks, we present a novel framework called “Enhanced Inpainting with Multi-head Attention and stacked long short-term memory (LSTM) Network” (E-Inpaint). This framework aims to re...

This study used a Quantum-Inspired Genetic Algorithm (QIGA) to select the proper functionality and reduce the dimensions, classification time, and computational cost of a learning dataset. QIGA reduces the complexity of solutions and improves the selection of the best features. The application of quantum principles, in particular the unpredictabili...

Deep visual data analysis from social network has become an increasingly important area of research. In fact, this form of assessment makes it viable to recognize new information on social users which incorporates emotions. In order to recognize users’ emotions and other latent attributes, most of the existing approaches have used textual data and...

As biometric technology evolves speedily, challenges increase to implement secure and accurate systems for personal identification and authentication as the highest target to achieve. Parallel security system evolution reveals continuously that monomodal biometrics is no longer exerted due to the lack of relevance in intruder’s identification. The...

Knowledge and concepts play a crucial role in human language processing. Human behavior varies in different environments, making it difficult to convey uniform definitions of these abstract notions. Furthermore, human language’s ambiguity can lead to different interpretations of a concept depending on the context. In knowledge representation, multi...

With the enormous growth of social data in recent years, sentiment analysis has gained increasing research attention and has been widely explored in various languages. Arabic language nature imposes several challenges, such as the complicated morphological structure and the limited resources, Thereby, the current state-of-the-art methods for sentim...

The detection of traffic signs in the natural scene requires a great deal of information due to the variations it undergoes over time for the output of the detection model to be effective and relevant. The amount of annotated data can range from a few hundred to thousands or even millions of examples, the availability of labeled data is often a cri...

With an emphasis on behavioral intrusion detection systems [BIDSs], this study investigates the field of intrusion detection in mobile ad hoc networks [MANETs]. Because they are dynamic and decentralized, MANETs are vulnerable to a range of security risks, such as infiltration attempts. In this situation, conventional intrusion detection techniques...

Reconstructing a 3D avatar of a human body from 2D images is not an easy task since it depends on several processing steps to enhance 3D acquisition devices input. Using camera-equipped drones with computer vision algorithms and photogrammetry tools to capture high-quality imagery data for 3D models reconstruction has become widespread recently. In...

The real threat to the privacy of a plain document exchanged over insecure channels is content manipulation or eavesdropping by unauthorized parties. To protect a transferred document, the architecture proposed in this paper offers encryption, authentication, and scrambling GAN with shuffle confusion (EAGAN) comprehensively with a relatively rapid...

In recent years, Optical character recognition (OCR) has experienced a resurgence of interest especially for contemporary Arabic data. In fact, OCR development for printed and handwritten Arabic script is still a challenging task. These challenges are due to the specific characteristics of the Arabic script. In this work, we attempt to address thes...

Research on training Generative Adversarial Networks (GANs) to create 3D human body avatars from 2D datasets is underway. Research done in this field shows promise and has paved the way for significant advancements in a variety of applications, including virtual reality, sports analysis, cinematography, surveillance, and cinematography. By avoiding...

The availability of publicly accessible datasets with identifiable facial images is essential for various research and development purposes. However, this wide access also underscores an increasing need for robust privacy protection. Regulations like the General Data Protection Regulation (GDPR) impose strict requirements for safeguarding personal...

Human Face receives major attention and acquires most of the efforts of the research and studies of Machine Learning in detection and recognition. In real-life applications, the problem of quick and rapid recognition of the Human Face is always challenging researchers to come out with powerful and reliable techniques. In this paper, we proposed a n...

Image denoising attempts to restore images that have been degraded. Historical document denoising is specially challenging because there is considerable background noise or variation in contrast and illumination in handwritten literature and the first times of the printing press. The main objective of this work is to propose a new method for histor...

For several decades, no satisfactory solutions have been provided to the problem of offline handwriting recognition. In the field of online recognition, researchers have had more successful performance, but the ability to extract dynamic information from static images has not been well explored yet. In this paper, we introduce a novel multi-lingual...

In this paper we study the oscillatory behavior of a new class of memristor based neural networks with mixed delays and we prove the existence and uniqueness of the periodic solution of the system based on the concept of Filippov solutions of the differential equation with discontinuous right-hand side. In addition, some assumptions are determined...

p>Fake account detection is a topical issue when many Online Social Networks encounter several issues caused by the growing number of unethical online activities. This study presents a new Quantum Beta-behaved Multi-Objective Particle Swarm Optimization (QB-MOPSO) algorithm for machine learning based Twitter fake accounts detection. The proposed ap...

Fake account detection is a topical issue when many Online Social Networks encounter several issues caused by the growing number of unethical online activities. This study presents a new Quantum Beta-behaved Multi-Objective Particle Swarm Optimization (QB-MOPSO) algorithm for machine learning based Twitter fake accounts detection. The proposed appr...

Machine learning is widely recognized as a key driver of technological progress. Artificial Intelligence (AI) applications that interact with humans require access to vast quantities of human image data. However, the use of large, real-world image datasets containing faces raises serious concerns about privacy. In this paper, we examine the issue o...

Biometric recognition is the process of verifying or classifying human characteristics in images or videos. It is a complex task that requires machine learning algorithms, including convolutional neural networks (CNNs) and Siamese networks. Besides, there are several limitations to consider when using these algorithms for image verification and cla...

Since Web 2.0 and the freedom to share information, perspectives, and opinions on global events, services, goods, etc., most of the content on social media platforms comes from users. Social media data includes user sentiment-related subjects. Due to its complexity, ambiguity, dialects, shortage of resources, and morphological diversity, little wor...

Image deblurring and super resolution attempts to restore images that have been degraded. We propose a joint technique for super resolution and deblurring to solve the problem of blur and low resolution in text images. This joint technique is based on the use of a Deep Convolutional Neural Network (Deep CNN). Deep CNN has achieved promising perform...

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

p>Human Face receives major attention and acquires most of the efforts of the research and studies of Machine Learning in detection and recognition. In real-life applications, the problem of quick and rapid recognition of the Human Face is always challenging researchers to come out with powerful and reliable techniques. In this paper, we proposed a...

p>The Ultra-Large Scale Software (ULSS) system is a novel generation of software systems that requires to be managed and developed across multiple organizations. Such a system challenges the existing agile methods and scaled agile methods as they address only the intra-organizational cooperation. In fact, for inter-organizational coordinations, the...

Deep data analysis for latent information prediction has become an increasingly important area of research. In order to predict users’ interests and other latent attributes, most of the existing solutions (works, studies) have used textual data and have obtained accurate results. However, little attention has been paid to visual data that have beco...

This paper proposes a 3D face alignment of 2D face images in the wild with noisy landmarks. The objective is to recognize individuals from their single profile image. We first proceed by extracting more than 68 landmarks using a bag of features. This allows us to obtain a bag of visible and invisible facial keypoints. Then, we reconstruct a 3D face...

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

In this work we prove some existence, global exponential stability and uniqueness results for measure pseudo almost periodic and automorphic solutions to a class of high-order Hopfield neural networks with delays. The main technique is based upon some appropriate composition theorems combined with the Banach contraction mapping principle. Finally,...

In this paper, we present a deep learning-based method for 3D face recognition. Unlike some previous works, our process does not rely on face representation methods as a proxy step to be accepted by Convolutional Neural Networks (CNNs). Applying 2D CNNs to irregular domains such as 3D meshes is challenging. Therefore, we employed 3D ShapeNets to re...

Believing that biometrics trends are moving to distant and contactless mode, in-air signature verification is nowadays considered as one of the principal users biometric identification in contactless mode allowing users identification by drawing their handwritten signature in the air. In-air signature verification is used in many applications like...

Estimating the semantic similarity between short texts plays an increasingly prominent role in many fields related to text mining and natural language processing applications, especially with the large increase in the volume of textual data that is produced daily. Traditional approaches for calculating the degree of similarity between two texts, ba...

Most evolutionary algorithms, including particle swarm optimization (PSO), use Pareto dominance as a major selection criterion and face significant challenges when dealing with many-objective problems. To tackle this issue, this paper proposes a novel algorithm, termed: Many- Objective PSO with Cooperative Agents (MaOPSO-CA). This exploits an Inver...

The fashion industry is at the brink of radical transformation. The emergence of Artificial Intelligence (AI) in fashion applications creates many opportunities for this industry and make fashion a better space for everyone. Interesting to this matter, we proposed a virtual try-on interface to stimulate consumers purchase intentions and facilitate...

Scene text recognition is an important part of scene understanding systems, hence lately the problem has gotten increasing attention. The popularity of this issue can be attributed to the numerous potential applications and future challenges. However, the scientific community has long concentrated on the CNN (Convolutional Neural Network) models in...

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...

p> Human Face receives major attention and acquires most of the efforts of the researches and studies of Machine Learning (ML) in detection and recognition. In real-life applications, the problem of quick and rapid recognition of the Human Face is always challenging the researchers to come out with powerful and reliable techniques. In this paper, w...

p> Human Face receives major attention and acquires most of the efforts of the researches and studies of Machine Learning (ML) in detection and recognition. In real-life applications, the problem of quick and rapid recognition of the Human Face is always challenging the researchers to come out with powerful and reliable techniques. In this paper, w...

p>For several decades, the offline handwriting recognition problem has escaped a satisfactory solution. In the field of online recognition, researchers have had more successful performance, but the ability to extract dynamic information from static images has not been well explored yet. In this paper, we introduce a novel multi-lingual word handwri...

p>For several decades, the offline handwriting recognition problem has escaped a satisfactory solution. In the field of online recognition, researchers have had more successful performance, but the ability to extract dynamic information from static images has not been well explored yet. In this paper, we introduce a novel multi-lingual word handwri...

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...