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Med Salim Bouhlel

Med Salim Bouhlel
SETIT · Sfax University

Professor

About

374
Publications
68,374
Reads
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1,544
Citations
Introduction
Mohamed Salim BOUHLEL is currently Full Professor at Sfax University, Tunisia. Head of the Research Lab SETIT since 2003. President and founder of the Tunisian association on HMI since 2013. Editor in Chief of the international Journals “HMI”, "MLHC and a dozen of special issues. Chairman of many international conferences research interests: Image processing, Telecom and HMI in which he has obtained more than 20 patents so far. More than 500 articles were published in IJ, IC & books.
Additional affiliations
January 2003 - December 2014
University of Sfax
Position
  • SETIT

Publications

Publications (374)
Article
Full-text available
Recent advances in sensor technology, including eye-gaze tracking, have introduced the opportunity to incorporate gaze into student modelling within an embodied learning context. The produced multimodal data is used to uncover cognitive, behavioural, and affective processes during the embodied learning activity. However, the use of eye-tracking dat...
Conference Paper
Advances in eye-gaze tracking technologies have presented the possibility of combining gaze features into students learning profiles. Building students profiles that support gaze information holds meaningful promise for embodied-based learning contexts. This paper examines the potential of developing a predictive model that incorporates student eye...
Chapter
The computer vision field is becoming very interesting. Several algorithms have been applied for object detection such as deep learning methods (Convolutional Neural Networks (CNN) for example) and clustering methods (Fuzzy C Means (FCM) for example), and have generated good results. However, some types of data (Hyperspectral Satellite Image (HSI)...
Conference Paper
This paper presents a process of knowledge Discovery from Data (KDD) applied on 2D Inverse Synthetic Aperture Radar (ISAR) images. This process is based on four crucial steps which are data acquisition, data pre-processing, data representation and data classification to make the final decision. We propose a new method for data representation based...
Article
Embodied cognition theory denotes that knowledge is incorporated into the body’s sensorimotor system, which facilitates learning and understanding abstract concepts. In this context, several interaction modalities have been introduced to design learning experiences that promote multisensory processing. This study examined the impacts of the type of...
Article
In this paper, is proposed a novel technique of Electrocardiogram (ECG) denoising. It is based on the application of Wavelet/Total-Variation (WATV) denoising approach in the domain of the Stationary Bionic Wavelet Transform (SBWT). It consists firstly in applying the SBWT to the noisy ECG signal for obtaining two noisy coefficients namedwtb1 and wt...
Article
Full-text available
Speech enhancement has gained considerable attention in the employment of speech transmission via the communication channel, speaker identification, speech-based biometric systems, video conference, hearing aids, mobile phones, voice conversion, microphones, and so on. The background noise processing is needed for designing a successful speech enha...
Conference Paper
Deep Learning for Hyperspectral Imaging Classification is a wonderful solution, despite a few fuzzification. Conventional neural networks are very effective for classification tasks which have allowed them to be used by a very large companies. In this paper, we present an approach to initialize the convolutional data: Firstly, an adaptive selection...
Conference Paper
Hyperspectral Satellite Images (HSI) presents a very interesting technology for mapping, environmental protection, and security. HSI is very rich in spectral and spatial characteristics, which are non-linear and highly correlated which makes classification difficult. In this paper, we propose a new approach to the reduction and classification of HS...
Conference Paper
Hyperspectral Imaging is a technology representing a scene via a large number of spectral bands. By increasing the amount of satellite information, the classification becomes more and more difficult. In recent years, deep learning has shown its effectiveness in classification and the identification of objects, especially via the Convolutional Neura...
Article
Full-text available
Hyperspectral satellite imagery (HSI) is an advanced technology for object detection because it provides a large amount of information. Thus, the classification of HSIs is very complicated, so the methods of reducing spectral or spatial information generally degrade the quality of classification. In order to solve this problem and guarantee faster...
Article
Classification of Hyperspectral Satellite Images (HSI) is a very important technology for object detection and cartography. Several problems can be detected, which make classification difficult (large size of the images, fusion between the classes, small amount of samples, etc.). Recently, several Convolutional Neural Networks (CNN-HSI) have been p...
Conference Paper
Hyperspectral Imaging is a technology representing a scene via a large number of spectral bands. By increasing the amount of satellite information, the classification becomes more and more difficult. In recent years, deep learning has shown its effectiveness in classification and the identification of objects, especially via the Convolutional Neura...
Article
This work presents the design of a new 2-2 programmable sigma delta modulator architecture, for different applications, this transformation design of the ΣΔ modulator low-pass, band-pass and high-pass or vice versa with loopbacks addition, which improved the linearity of the converter and reduced the quantization noise. In this work, the MASH struc...
Article
Full-text available
Nowadays, a variety of cryptosystem based on the chaos theory have been proposed. In this paper, we propose a new scheme encryption for Magnetic Resonance Imaging (MRI); medical images, using the chaos theory to define a dynamic chaotic Look-Up Table (LUT). Theoretic analyses and simulation results show that our scheme is secure and efficient. Also...
Article
Full-text available
The combination of compression and visualization is mentioned as perspective, very few articles treat with this problem. Indeed, in this paper, we proposed a new approach to multiresolution visualization based on a combination of segmentation and multiresolution mesh compression. For this, we proposed a new segmentation method that benefits the org...
Article
Traditional neural networks are very diverse and have been used during the last decades in the fields of data classification. These networks like MLP, back propagation neural networks (BPNN) and feed forward network have shown inability to scale with problem size and with the slow convergence rate. So in order to overcome these numbers of drawbacks...
Article
Montessori considers as an effective method that is commonly used in nurseries to improve the mental performance and develop the cognitive skills toward children. Tangible user interfaces (TUI) is an effective tool that allows interaction with physical objects in a way that makes this interaction augmented through embedded computation. This paper p...
Article
Researches on psychology and affective state recognition demonstrated that emotion is equally transmitted through the body and the face in most cases. In this line, the purpose of this work is to identify the affective state of the individual through his facial expression and upper body gesture. We are looking to recognize six emotions: anger, anxi...
Article
Detection and classification with traditional neural networks methods such as multilayer perceptron (MLP), feed forward network and back propagation neural networks show several drawbacks including the rate of convergence and the incapacity facing the problems of size of the image especially for radar images. As a result, these methods are being re...
Article
Detection and classification with traditional neural networks methods such as multilayer perceptron (MLP), feed forward network and back propagation neural networks show several drawbacks including the rate of convergence and the incapacity facing the problems of size of the image especially for radar images. As a result, these methods are being re...
Article
Embodied learning pedagogy highlights the interconnections between the brain, body, and the concrete environment. As a teaching method, it provides means of engaging the physical body in multimodal learning experiences to develop the students’ cognitive process. Based on this perspective, several research studies introduced different interaction mo...
Chapter
The increasing use of 3D models in many areas lead us to think about the impact of the different distortions that can affect the 3D object during the rendering process. These deformations are usually evaluated using geometric metrics, which have not a good correlation with human judgment, while the visual perceptual quality of 3D models is necessar...
Conference Paper
Implementing machine learning techniques is receiving considerable attention in the educational technology research field. Different systems and techniques were proposed to predict student performance and gain insights regarding their learning needs. However, to the best of our knowledge, no previous research studies explored predicting student per...
Chapter
Full-text available
Human actions recognition (HAR) and understanding become very popular topics in the field of computer vision and signal processing. The purpose of human activities recognition is to automatically examine and characterize actions from a video sequence. The main goal of a HAR system is to identify simple actions of everyday life (like walking, runnin...
Chapter
Full-text available
In this chapter, we will detail a new speech enhancement technique based on Lifting Wavelet Transform (LWT) and Artifitial Neural Network (ANN). This technique also uses the MMSE Estimate of Spectral Amplitude. It consists at the first step in applying the LWTto the noisy speech signal in order to obtain two noisy details coefficients, cD1 and cD2...
Article
Classification of Hyperspectral Satellite Images (HSI) is a very important technology for object detection and cartography. Several problems can be detected, which make classification difficult (large size of the images, fusion between the classes, small amount of samples, etc.). Recently, several Convolutional Neural Networks (CNN-HSI) have been p...
Article
Behavior analysis is an important yet challenging task on computer vision area. However, human behavior is still a necessity in differents sectors. In fact, in the increase of crimes, everyone needs video surveillance to keep their belongings safe and to automatically detect events by collecting important information for the assistance of security...
Conference Paper
Embodied learning defines a contemporary pedagogical theory focusing on ensuring an interactive learning experience through full-body movement. Within this pedagogy, several studies in Human-Computer Interaction have been conducted, incorporating gestures, and physical interaction in different learning fields. This paper presents the design of a mu...
Article
Image classification by the convolutional neural network (CNN) has shown its great performances in recent years, in several areas, such as image processing and pattern recognition. However, there is still some improvement to do. The main problem in CNN is the initialisation of the number and size of the filters, which can obviously change the resul...
Conference Paper
Hyperspectral Imaging is a technology representing a scene via a large number of spectral bands. By increasing the amount of satellite information, the classification becomes more and more difficult. In recent years, deep learning has shown its effectiveness in classification and the identification of objects, especially via the Convolutional Neura...
Chapter
Deep Learning for Hyperspectral Imaging Classification is a wonderful solution, despite a few fuzzification. Conventional neural networks are very effective for classification tasks which have allowed them to be used by a very large companies. In this paper, we present an approach to initialize the convolutional data: Firstly, an adaptive selection...
Conference Paper
Hyperspectral Satellite Images (HSI) presents a very interesting technology for mapping, environmental protection, and security. HSI is very rich in spectral and spatial characteristics, which are non-linear and highly correlated which makes classification difficult. In this paper, we propose a new approach to the reduction and classification of HS...
Conference Paper
Full-text available
In this paper we propose a new technique of Electrocardiogram (ECG) denoising. This technique is based on Lifting Wavelet Transform (LWT) and Total variation based denoising technique using majorization-minimization. It consists at the first step in applying the LWT to the noisy ECG signal in order to obtain three noisy coefficients, cA2, cD2 and c...
Chapter
Hyperspectral Satellite Images (HSI) presents a very interesting technology for mapping, environmental protection, and security. HSI is very rich in spectral and spatial characteristics, which are non-linear and highly correlated which makes classification difficult. In this paper, we propose a new approach to the reduction and classification of HS...
Article
Full-text available
Ensuring the confidentiality of any data exchanged always presents a great concern for all communication instances. Technically, encryption is the ideal solution for this task. However, this process must deal with the progress of the cryptanalysis that aims to disclose the information exchanged. The risk increases due to the need for a dual transmi...
Article
Full-text available
The recognition of human activities is usually considered to be a simple procedure. Problems occur in complex scenes involving high speeds. Activity prediction using Artificial Intelligence (AI) by numerical analysis has attracted the attention of several researchers. Human activities are an important challenge in various fields. There are many gre...
Article
The recognition of human activities is usually considered to be a simple procedure. Problems occur in complex scenes involving high speeds. Activity prediction using Artificial Intelligence (AI) by numerical analysis has attracted the attention of several researchers. Human activities are an important challenge in various fields. There are many gre...
Article
Due to the recent development of machine learning and sensor innovations, hand gesture recognition systems become promising for the digital entertainment field. In this paper, we propose a dynamic hand gesture recognition approach using touchless hand motions over a Leap Motion device. First, we analyze the sequential time series data gathered from...
Article
Full-text available
Hyperspectral satellite imagery (HSI) is an advanced technology for object detection because it provides a large amount of information. Thus, the classification of HSIs is very complicated, so the methods of reducing spectral or spatial information generally degrade the quality of classification. In order to solve this problem and guarantee faster...
Conference Paper
Hand gesture recognition has become one of the most interesting means of contactless human-computer interaction. There is significant importance for commanding medical images during surgical procedures by the mean of touchless hand gestures for reducing the time of surgery and the risk of contamination. In this work, we used the Leap Motion Control...
Article
Recently, Hand-Gesture-Recognition (HGR) systems has appreciably change the way of interaction between humans and computers thanks to advanced sensor technologies like the Leap-Motion-Controller (LMC). Despite the success achieved by many state-of-the-art methods, they have not worked on the rich temporal information existing in the sequential hand...
Article
Full-text available
This paper proposes an efficient scheme to reduce the pre-correlation bandwidth effect in the global navigation satellite system (GNSS) receiver filtering process. It is mainly based on the application of a spectral transformation to the satellite-emitted signal that effectively reduces its band. At the receiver's end, this operation causes the spr...
Chapter
High definition and 3D telemedicine offer a compelling mechanism to achieve a sense of immersion and contribute to an enhanced quality of use. 3D mesh perceptual quality is crucial for many applications. Although there exist some objective metrics for measuring distances between meshes, they do not integrate the characteristics of the human visual...
Chapter
Fall is a major health problem, especially among elderly people living alone at home. This age group is characterized by a loss of physical and motor skills, balance and posture disorder, and a reduction in daily activities. These factors are the main cause of falling. However, it is important to design technologies that prevent falls and can help...
Chapter
Automatic Speech Emotion Recognition (SER) is a current research topic in the field of Human Computer Interaction (HCI) with a wide range of applications. The purpose of speech emotion recognition system is to automatically classify speaker's utterances into different emotional states such as disgust, boredom, sadness, neutral, and happiness. The s...
Article
Full-text available
People who are blind or low vision need to follow activities routines for their mental and physical health to minimize the risk of suffering from bleeding in articulation but they have problems due to difficulties and inaccessibility of displacement. This paper introduces and evaluate a set of exercises to improve the bodily movement and stability...
Article
Full-text available
In this paper, a new speech compression technique is proposed. This technique applies a Psychoacoustic Model and a general approach for Filter Bank Design using optimization. It is evaluated and compared with a compression technique using a MDCT (Modified Discrete Cosine Transform) Filter Bank of 32 Filters and a Psychoacoustic Model. This evaluati...
Article
Convolutional neural networks (CNN) can learn deep feature representation for hyperspectral imagery (HSI) interpretation and attain excellent accuracy of classification if we have many training samples. Due to its superiority in feature representation, several works focus on it, among which a reliable classification approach based on CNN, used filt...
Article
Convolutional neural networks (CNN) can learn deep feature representation for hyperspectral imagery (HSI) interpretation and attain excellent accuracy of classi¯cation if we have many training samples. Due to its superiority in feature representation, several works focus on it, among which a reliable classi¯cation approach based on CNN, used¯lters...
Article
Convolutional neural networks (CNN) can learn deep feature representation for hyperspectral imagery (HSI) interpretation and attain excellent accuracy of classi¯cation if we have many training samples. Due to its superiority in feature representation, several works focus on it, among which a reliable classi¯cation approach based on CNN, used¯lters...
Article
Full-text available
Human behavior has been always an important factor in social communication. The human activity and action recognition are all clues that facilitate the analysis of human behavior. Human action recognition is an important challenge in a variety of application including human-computer interaction and intelligent video surveillance to enhance security...
Book
Full-text available
This Book Includes the Proceedings of the Eighth International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT’18) held jointly in Genoa, Italy and Hammamet, Tunisia on December 18–20, 2018, Volume 2 Covers a range of topics in Electronic, Signal, Image and Video Processing, Telecommunications and Ne...
Book
Full-text available
Proceedings of the eighth International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT’18) held jointly in Genoa–Italy, Hammamet–Tunisia in December 18-20, 2018, Volume 1 Covers themes in Electronic, Signal, Image and Video processing, Telecommunications and Networks, and Computer Science Written by...
Article
Full-text available
Human action recognition is a computer vision task. The evaluation of action recognition algorithms relies on the proper extraction and learning of the data. The success of the deep learning and especially learning layer by layer led to many imposing results in several contexts that include neural network. Here the Recurrent Neural Networks (RNN) w...
Book
Over the past decade, with the progress in technology, there has emerged various needs for users to get more interactive with Web applications. Commercial web services have spread the use of rich interfaces to provide users with a meaningful interaction with these applications. Nevertheless, the dynamic nature of the context of interaction imposes...
Article
To analyze a tennis video sequence at a higher semantic level, the first step is to determine the position of the court. Thus, it is required to track the court in the scene. In this article, we proposed a new automatic system for tennis court detection and tracking in real time. Our system comprises a structural analysis system that extracted the...
Article
Convolutional neural networks (CNN) can learn deep feature representation for hyperspectral imagery (HSI) interpretation and attain excellent accuracy of classi¯cation if we have many training samples. Due to its superiority in feature representation, several works focus on it, among which a reliable classi¯cation approach based on CNN, used¯lters...
Article
Full-text available
In this study, the authors propose a new method that eliminates ambiguity in global navigation satellite system (GNSS) code acquisition and tracking significantly. It is based on the use of a specified locally generated (SLG) pseudo-random noise code that can be correlated with any received binary offset carrier sine- or cosine-modulated signal. As...
Preprint
Full-text available
The amount of audio-visual information has increased dramatically with the advent of High Speed Internet. Furthermore, technological advances in recent years in the field of information technology, have simplified the use of video data in various fields by the general public. This made it possible to store large collections of video documents into...
Article
Full-text available
Image classification by the convolutional neural network (CNN) has shown its great performances in recent years, in several areas, such as image processing and pattern recognition. However, there is still some improvement to do. The main problem in CNN is the initialisation of the number and size of the filters, which can obviously change the resul...