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Publications (49)
Language impairment is a key biomarker for neurodegenerative diseases such as Alzheimer's disease (AD). With the rapid growth of Large Language Models, natural language processing (NLP) has become a preferred modality for the early prediction of AD from speech. In this work, we propose a two-stage process for early detection of AD from transcriptio...
Alzheimer's disease (AD) is a chronic and irreversible neurological disorder, making early detection essential for managing its progression. This study investigates the coherence of SHAP values with medical scientific truth. It examines three types of features: clinical, demographic, and FreeSurfer extracted from MRI scans. A set of six ML classifi...
Detecting and tracking(D &T) moving objects presents important preliminary steps in the processes of object recognition, contextual analysis, and indexing within visual surveillance systems. D &T refer to the procedure of identifying and monitoring the presence and motion of individuals within a specified area, often using employing machine learnin...
Human interaction and computer vision converge in the realm of Human Activity Recognition (HAR), which is a research field dedicated to the creation of automated systems capable of observing and categorizing human activities. This domain closely aligns with machine learning, involving the development of algorithms and models adept at learning to re...
Alzheimer’s patients necessitate consistent support from caregivers or family members, highlighting the urgency for advanced technologies to aid in their daily lives through early disease detection. Consequently, there has been substantial research and development of machine learning-based systems aimed at assisting Alzheimer’s patients. However, e...
Alzheimer’s disease is considered as one of the most well-known illnesses in the elderly. It is a neurodegenerative and irreversible brain disorder that slowly destroys memory, thinking ability, and ultimately the ability to perform even basic daily tasks. In fact, people suffering from this disorder have difficulty remembering events, recognizing...
The problem of road safety is an important issue for human society. The challenge is to reduce the number of accidents, and consequently the number of fatalities and injuries on roads caused by the hypovigilance. The objective of this work is to concept a multimodal driving assistance system able to detect different categories of lack of vigilance...
Alzheimer’s disease is one of the most well-known diseases among the elderly. It is a neuro-degenerative and irreversible brain disease that gradually erodes memory, thinking skills, and, eventually, the capacity to do even basic daily activities. Therefore, patients should be aided at all times in carrying out their daily tasks. In this study, we...
One of the most recent challenging tasks in computer vision is Human Activity Recognition (HAR), which aims to analyze and detect the human actions for the benefit of many fields such as video surveillance, behavior analysis and healthcare. Several works in the literature are based on the extraction and analysis of human skeletons in the aim of act...
People with Alzheimer’s disease find it difficult to perform their Activities of Daily Living (ADLs) due to limited abilities in cognitive functioning. They cannot remember the correct sequence of the performed activity steps, and sometimes they can spend a lot of time in an activity without finishing it. Therefore, to be successful with ADLs, they...
This paper introduces a novel approach for human activities recognition (HAR) based on body articulations (joints) that represent the connection between bones in the human body which join the skeletal system such as the knee, shoulder and hand, and which are made to allow different degrees and types of movement. To implement our system, we used Pos...
Fatigue and drowsiness are among the main causes of traffic accidents, just behind excessive speed and alcoholism. This paper deals with the problem of road safety. It attempts to present a driver vigilance monitoring system based on a video approach. This work aims at creating an assistive driving application employing eyes closure duration and he...
Driver fatigue is a serious problem causing thousands of road accidents each year. The major challenge in the field of accident avoidance systems is the development of technologies for detecting or preventing drowsiness at the wheel. In this paper, we present a novel approach for fatigue estimation based on the design of an intelligent seat able to...
The vision based on hand gesture recognition is one of the key challenges in behavior understanding and computer vision. It offers to machines the possibility of identifying, recognizing and interpreting hand gestures in the aim of controlling certain devices, to monitor certain human activities or interacting with certain human machine interfaces...
This paper deals with the problem of vigilance level monitoring. A novel method of hypovigilance detection is presented in this work. It is based on the analysis of eyes’ blinking and head posture. The fusion task of both systems is achieved by the fuzzy logic technique which allows us to obtain five vigilance levels. This paper contains two key co...
This paper aims at addressing a challenging research in both fields of the wavelet neural network theory and the pattern recognition. A novel architecture of the wavelet network based on the multiresolution analysis (MRWN) and a novel learning algorithm founded on the Fast Wavelet Transform (FWTLA) are proposed. FWTLA has numerous positive sides co...
This work aims to recognize the six basic emotions using facial expression and improve the classification in term of time and space memory. We started with the idea that emotions can be absolutely distinctive and from a single feature we can recognize emotion and therefore we save time in learning data.
We also noted that the similarity between th...
Speech recognition is a specialized pattern recognition task with several applications such as vocal command system, dictating machines, and understanding systems. In recent years, research on pattern recognition has increased by developing various methods and algorithms for different applications. In this paper, we proposed a novel training algori...
This paper presents a novel hand posture recognizer based on separator wavelet networks (SWNs). Aiming at creating a robust and rapid hand posture recognizer, we have contributed by proposing a new training algorithm for the wavelet network classifier based on fast wavelet transform (FWN). So, the contribution resides in reducing the number of WNs...
In last years, the emergence of 3D shape in face recognition is due to its robustness to pose and illumination changes. These attractive benefits are not all the challenges to achieve satisfactory recognition rate. Other challenges such as facial expressions and computing time of matching algorithms remain to be explored. In this context, we propos...
Driving security is an important task for human society. The major challenge in the field of accident avoidance systems is the driver vigilance monitoring. The lack of vigilance can be noticed by various ways, such as, fatigue, drowsiness and distraction. Hence, the need of a reliable driver’s vigilance decrease detection system which can alert dri...
This paper aims at developing a novel approach for speech recognition based on wavelet network learnt by fast wavelet transform (FWN) including a fuzzy decision support system (FDSS). Our contributions reside in, first, proposing a novel learning algorithm for speech recognition based on the fast wavelet transform (FWT) which has many advantages co...
Nowadays the amount of imaging data is rapidly increasing with the widespread dissemination of picture archiving in medical systems. Effective image retrieval systems are required to manage these complex and large image databases. Indexing medical images become, for clinical applications, an essential and effective tool which assists the monitoring...
Supervised machine learning is an important field with many immediate applications. As a result, there is an increasing number of public tools with a diversity of learning approaches. In this paper we propose a new architecture of wavelet network classifier learnt by a fast wavelet transform (FWN). This classifier is well suited for data classifica...
A drowsy driver detection system based on a new method for head posture estimation is proposed. In the first part, we introduced six possible models of head positions that can be detected by our algorithm which is explained in the second part. Indeed, there are three key stages characterizing our method: First of all, we proceed with driver’s face...
In this paper we present a novel hand posture recognizer based on wavelet network learnt by fast wavelet transform (FWN) including a fuzzy decision support system (FDSS). Our contribution in this paper resides in proposing a new classification way for the FWN classifier. The FWN having an hybrid architecture (using as activation functions both wave...
This paper attempts to present a vision-based interface which interacts with computers by hand gesture recognition. This work aims at creating a natural and intuitive application employing both static and dynamic hand gestures. The proposed application can be summarized in three main steps: hands detection in a video, hands tracking and converting...
The automatic interpretation of gestures based on computer vision offers new possibilities to interact with machines. These interactions are more natural and more intuitive than those with classical devices. In this paper, we are interested in using our hands as pointing devices to remotely ordering computers. The proposed application can be summar...
In this paper, a novel learning algorithm of wavelet networks based on the Fast Wavelet Transform (FWT) is proposed. It has many advantages compared to other algorithms, in which we solve the problem in previous works, when the weights of the hidden layer to the output layer are determined by applying the back propagation algorithm or by direct sol...
This paper presents a new approach of face recognition based on wavelet network using 2D fast wavelet transform and multiresolution analysis. This approach is divided in two stages: the training stage and the recognition stage. The first consists to approximate every training face image by a wavelet network. The second consists in recognition of a...
Taking advantage of both the scaling property of wavelets and the high learning ability of neural networks, wavelet networks have recently emerged as a powerful tool in many applications in the field of signal processing such as data compression, function approximation as well as image recognition and classification. A novel wavelet network-based m...
Image classification is an important task in computer vision. In this paper, we propose a supervised method for image classification based on a fast beta wavelet networks (FBWN) model. First, the structure of the wavelet network is detailed. Then, to enhance the performance of wavelet networks, a novel learning algorithm based on the Fast Wavelet T...
A wavelets neural network is a hybrid classifier composed of a neuronal contraption and wavelets as functions of activation. Our approach of face recognition is divided in two parts: the training phase and the recognition phase. The first consists in optimizing a wavelets neural network for every training picture face. A new technique of training o...
In this paper, we present a direct solution method based on wavelet networks for image compression. Wavelet networks are a combination of radial basis function (RBF) networks and wavelet decomposition, where radial basis functions were replaced by wavelets. The results show that the wavelet networks approach succeeded to improve high performances i...
For many years, we have witnessed an increasing growth in the need of numeric pictures (whether stationary or animate) in numerous fields such as telecommunications, multimedia diffusion, medical diagnosis, telesurveillance, meteorology, robotics, etc. However, this type of data represents a huge mass of information that is difficult to transmit an...