Sidi Ahmed Mahmoudi

University of Mons · Department of Computer Science

Computer vision tasks such as object detection and segmentation rely on the availability of extensive, accurately annotated datasets. In this work, We present CIA, a modular pipeline, for (1) generating synthetic images for dataset augmentation using Stable Diffusion, (2) filtering out low quality samples using defined quality metrics, (3) forcing...

Heterogeneous systems deliver high computing performance when effectively utilized. It is crucial to execute each application on the most suitable device while maintaining system balance. However, achieving equal distribution of the computing load is challenging due to variations in computing power and device architectures within the system. Moreov...

The growing demand for advanced tools to ensure safety in railway construction projects highlights the need for systems that can smoothly integrate and analyze multiple data modalities, such as multimodal learning algorithms. The latter, inspired by the human brain’s ability to integrate many sensory inputs, has emerged as a promising field in arti...

The rapid growth of e-commerce has placed considerable pressure on customs representatives, prompting advanced methods. In tackling this, Artificial intelligence (AI) systems have emerged as a promising approach to minimize the risks faced. Given that the Harmonized System (HS) code is a crucial element for an accurate customs declaration, we propo...

Load balancing plays a critical role in ensuring system stability and optimal performance, and as such, it has been a subject of extensive research across diverse computing domains, particularly in heterogeneous systems. Such systems integrate various computing devices with distinct architectures and computational power, each designed to execute a...

In the era of artificial intelligence (AI), the deployment of intelligent systems for autonomous decision making has surged across diverse fields. However, the widespread adoption of AI technology is hindered by the risks associated with ceding control to autonomous systems, particularly in critical domains. Explainable artificial intelligence (XAI...

Video surveillance and image acquisition systems represent one of the most active research topics in computer vision and smart city domains. The growing concern for public and workers’ safety has led to a significant increase in the use of surveillance cameras that provide high-definition images and even depth maps when 3D cameras are available. Co...

Screening for coronary artery disease is a major health issue, knowing that the most common cause of death in industrialized countries is cardiovascular pathology (coronary artery disease, stroke, other cardiovascular diseases). Computer Aided Diagnosis systems (CADx) can assist cardiologists to and play a key role in detecting abnormalities and tr...

Screening for coronary artery disease is a major health issue, knowing that the most common cause of death in industrialized countries is cardiovascular pathology (coronary artery disease, stroke, other car-diovascular diseases). Computer Aided Diagnosis systems (CADx) can assist cardiologists to and play a key role in detecting abnormalities and t...

Deep Learning (DL) is increasingly used in Cloud Computing services, where almost unlimited computing resources are available to accelerate the training, testing, and deployment of models. However, it is important to mention the challenges that developers may face when using a Cloud services, for instance the variation of application requirements o...

Indexing images by content is one of the most used computer vision methods, where various techniques are used to extract visual characteristics from images. The deluge of data surrounding us, due the high use of social and diverse media acquisition systems, has created a major challenge for classical multimedia processing systems. This problem is r...

During the last years, deep learning (DL) models have been used in several applications with large datasets and complex models. These applications require methods to train models faster, such as distributed deep learning (DDL). This paper proposes an empirical approach aiming to measure the speedup of DDL achieved by using different parallelism str...

With the emergence of smartphones, video surveillance cameras, social networks, and multimedia engines, as well as the development of the internet and connected objects (the Internet of Things—IoT), the number of available images is increasing very quickly. This leads to the necessity of managing a huge amount of data using Big Data technologies. I...

Distributed Deep Learning (DDL) is using a multi-node architecture to apply Deep Learning (DL) counter to Federated Deep Learning (FDL) where entities keep their data and contribute to a common DL task like training a model. The more nodes there are, the more network traffic increases in DDL which requires more time to distribute the load and to ap...

Recently, Artificial Intelligence (AI) and more particularly Deep Learning (DL) applications gained significant importance in several domains such as computer vision, robotics, medical imaging, etc. Despite the excellent results of AI models, in terms of precision and performance, their decisions are not always interpretable and explainable, which...

The field of biometrics represents an important domain and is currently undergoing extensive research to improve data security. Among the most used biometric modalities, we find the iris which, is specific and adequate. It is unique for each human being. Iris identification is used at international airports, sea, and land borders. In this article,...

Deep learning presents an efficient set of methods that allow learning from massive volumes of data using complex deep neural networks. To facilitate the design and implementation of algorithms, deep learning frameworks provide a high-level programming interface. Based on these frameworks, new models, and applications are able to make better and be...

In this work, we proposed an Explainable model based on Deep Learning for fast COVID-19 screening in chest CT images. We first collected a database of 360 COVID and Non-COVID images at the Tlemcen hospital in Algeria. This database was merged with two other public datasets (the first one has been collected from several articles published on medRxiv...

Nowadays, cancer is one of the leading causes of human death in the world. In 2020, breast carcinoma represented 11.7% of cancers reported in the female world population. Medical imaging is crucial for breast cancer screening and occupies a large place in diagnosis. Early screening with digital mammography is the key factor of successful detection...

Introduction. In the field of research, we are familiar to employ ready-to-use commercial solutions. This bibliographic review highlights the various technological paths that can be used in the context of agriculture digitalization and illuminates the reader on the capacities and limits of each one. Literature. Based on a literature review that we...

Fast and efficient collaboration among researchers is a crucial task to advance effectively in Covid-19 research. In this chapter, we present a new collaborative platform allowing to exchange and share both medical benchmark datasets and developed applications rapidly and securely between research teams. This platform aims to facilitate and encoura...

The latest advances of deep learning and particularly convolutional neural networks (CNNs) have proven more than once their high accuracy in disease detection. In this chapter, we propose a new deep learning-based approach for COVID-19 detection from chest X-ray images. The proposed approach applies, in an efficient way, the techniques of transfer...

With the advent of the digital age and more specifically videos, a huge amount of data is produced every day such as television archiving, video surveillance, etc. Faced with the need to keep control over this content, to be able to analyze it, classify it and many other applications, the need for algorithms capable of performing this task efficien...

Wheat variety recognition and authentication are essential tasks of the quality assessment in the grain chain industry, especially for seed testing and certification processes. Recognition and authentication by direct visual analysis of grains are still achieved manually. The automatic approach, based on computer vision and machine learning classif...

Landslides are phenomena that cause significant human and economic losses. Researchers have investigated the prediction of high landslides susceptibility with various methodologies based upon statistical and mathematical models, in addition to artificial intelligence tools. These methodologies allow to determine the areas that could present a serio...

The latest advances in machine learning and in particular with convolutional neurons (CNN) have proven more than once their great accuracy in the detection of diseases. In this paper, we present a new approach for COVID-19 detection from chest X-ray images using Deep Learning algorithms. An efficient process consisting of techniques of transfer lea...

Smartphones, particularly iPhone, can be relevant instruments for researchers because they are widely used around the world in multiple domains of applications such as animal behavior. iPhone are readily available on the market, contain many sensors and require no hardware development. They are equipped with high performance inertial measurement un...

In a growing population context with less resources of soil and water, the irrigated agriculture allows us to increase the yield and the production of several crops in order to meet the high requirements of demands of food and fibers. Efficiently, an irrigation system should correctly evaluate the amount of water and also the timing, when apply cer...

Landslides are phenomena widely present around the world and responsible each year of numerous life loss and extensive property damage. Researchers have developed various methodologies to identify area of high susceptibility of landslides. However, these methodologies cannot predict 'when' landslides are going to take place. Indeed, Wireless Sensor...

Smart Poultry acquires data from aviaries by means of sensor network at reduced intervals of time (every minute) that generatehundred thousands of data. The conjunction of Internet of Things and Artificial Intelligence open the field of the real-time mon-itoring of poultry, advance analytics and automation if data is from high quality. In this pape...

Artificial intelligence (AI) and Internet of things (IoT) have progressively emerged in all domains of our daily lives. Nowadays, both domains are combined in what is called artificial intelligence of thing (AIoT). With the increase of the amount of data produced by the myriad of connected things and the large wide of data needed to train Artificia...

Climatic chamber are enclosures where the ambient conditions, i.e. the temperature and humidity, are finely controlled. These speakers can play multiple roles such as the cultivation of plants (phytotron), the breeding of insects or habitat for exotic animals. In this paper, we propose a versatile and automated modular climatic enclosure system tha...

The detection, counting, and precise segmentation of white blood cells in cytological images are vital steps in the effective diagnosis of several cancers. This paper introduces an efficient method for automatic recognition of white blood cells in peripheral blood and bone marrow images based on deep learning to alleviate tedious tasks for hematolo...

Biometric iris recognition is a very advanced technology for the security and identification of individuals, this technology is widely used by national and multinational companies in terms of data protection and security. An iris recognition system requires an adapted architecture and specific because it generally recommends five steps: image acqui...

The last few years have been marked by the presence of very large sets of images and videos in our everyday lives. These multimedia objects have a very fast frequency of creation and sharing since images and videos can come from different devices such as smartphones, satellites, cameras, or drones. They are generally used to illustrate objects in d...

Breast cancer screening is a public health issue. Knowing that one in nine women will be affected by this disease, the detection of its first signs is crucial. Computer Assisted Diagnostic Systems (CADx) can help the radiologist to read mammograms and play a key role in the early detection of breast cancer. Nowadays, machine learning algorithms are...

Screening for coronary artery disease is a major health issue, knowing that the most common cause of death in industrialized countries is cardiovascular pathology (coronary artery disease, stroke, other cardiovascular disease). Computer aided diagnosis systems (CADx) assist cardiologists and play a key role in detecting abnormalities and treating c...

Digital Phenotyping is a emergent science mainly based on imagery techniques. The tremendous amount of data generated needs important cloud computing for their processing. The coupling of recent advance of distributed databases and cloud computing offers new possibilities of big data management and data sharing for the scientific research. In this...

In the era of Big data, data-driven farming is changing the agricultural businesses thanks to the use of modern technologies such as the Internet of Things (IoT) sensors, drones, and farm monitoring. IoT devices produce a massive amount of precious agri-data, which are collected and analyzed in real-time using innovative application tools. This com...

Nowadays, we are in the era of advanced technologies where tremendous amount of data is produced by multiple sources such as sensors, devices, social media, user experiences, etc. Furthermore, this raw data has a low value, and major part is not really useful or important for business. One way to give an added value to this stored data is to extrac...

Plusieurs modèles de CNN (InceptionV3, Xception, VGG16, …) ont été testés sur des bases de données publiques constituées d'images mammographiques annotées (MIAS, INbreast, DDSM, ...) dont la performance a été améliorée grâce à différentes actions combinées visant à augmenter les données d'apprentissage. L'objectif consiste à examiner l'efficacité d...

Breast tumor segmentation in medical images is a decisive step for diagnosis and treatment follow-up. Automating this challenging task helps radiologists to reduce the high manual workload of breast cancer analysis. In this paper, we propose two deep learning approaches to automate the breast tumor segmentation in dynamic contrast-enhanced magnetic...

The process of image retrieval presents an interesting tool for different domains related to computer vision such as multimedia retrieval, pattern recognition, medical imaging, video surveillance and movements analysis. Visual characteristics of images such as color, texture and shape are used to identify the content of images. However, the retriev...

Les réseaux de capteurs sans fil, l’Internet des objets et l’intelligence artificielle apportent conjointement un appui non négligeable dans la gestion quotidienne des infrastructures agricoles et contribuent à relever les défis de demain liés à la raréfaction des ressources, l’augmentation de la population ainsi que les changements climatiques.

Internet of things (IoT) is a massively growing industry in todays times. In fact, more and more devices able to interact together have been recently designed and launched in the market. All the objects that we use in our daily lives are becoming smarter. Everybody agrees that the education has been dramatically changed by the internet over the pas...

Smart farming is one of the most diverse researches. In addition, the quantity of data to be stored and the choice of the most efficient algorithms to process are important elements in this field. The storage of collected data from Internet of Things (IoT), existing on distributed, local databases and open data needs particular infrastructure to fe...

The last few years have been strongly marked by the presence of multimedia data (images and videos) in our everyday lives. These data are characterized by a fast frequency of creation and sharing since images and videos can come from different devices such as cameras, smartphones or drones. The latter are generally used to illustrate objects in dif...

Internet of Things is becoming widely present in our daily life. In fact, more and more devices able to interact together have been recently designed and launched in the market. Learning Internet of Things technologies is becoming unavoidable in education. In this paper, we propose a practical approach allowing to progressively learn, by practice t...

Video processing and more particularly motion tracking algorithms present a necessary tool for various domains related to computer vision such as motion recognition, depth estimation and event detection. However, the use of high definitions videos (HD, Full HD, 4K, etc.) cause that current implementations, even running on modern hardware, no longer...

The process of image retrieval presents a great interest in the domains of computer vision, video-surveillance, etc. Visual characteristics of image such as color, texture, shape are used to identify the content of images. However, the retrieving process becomes very challenging due to the hard management of large databases in terms of storage, com...

Heterogeneous systems which are composed of multiple CPUs and GPUs are more rnand more attractive as platforms for high performance computing. With thern evolution of General Purpose computation on GPU (GPGPU) and correspondingrn programming frameworks (OpenCL and CUDA), more applications are using GPUs rnas a co-processor to achieve performance th...

The goal of this project is to develop a cloud platform for indexing large-scale images by the content using the technique of Big Data such as Hadoop, Spark, etc. The techniques of Machine and Deep Learning will be used for improving the accuracy of learning and retrieval phases. Within our platform, the user can provide the query image, the result...

the last few years have been strongly marked by the great evolution of artificial intelligence domain due to arrival of new methods of Machine and Deep learning. According to literature i , investments in artificial intelligence have increased by 300% with a turnover that should be multiplied by 5.9x in 2020. The main reason for this interest is th...

Large-scale image retrieval is one of the critical technological fields using Big Data effectively. Content-Based Image Retrieval (CBIR) has become the popular method, which detects and

the last few years have been marked by the presence of multimedia data (images and videos) in our everyday lives. The latter are characterized by a fast frequency of creation and sharing since images and videos can come from different devices such as cameras, smartphones or drones. They are generally used to illustrate objects in different situatio...

High Performance Computing Course

Cours Multimedia Rertrieval and Indexation: Cloud and GPU for Multimedia Retrieval

GPU Programming tools

High Performance Computing : Introduction to Cloud Computing