François Bourzeix

• Manager at Moroccan Foundation for Advanced Research Science and Innovation

This study addresses the problem of early detection of leaf miner infestations in chickpea crops, a significant agricultural challenge. It is motivated by the potential of hyperspectral imaging, once properly combined with machine learning, to enhance the accuracy of pest detection. Originality consists of the application of these techniques to chi...

Africa’s rapidly growing population is driving unprecedented demands on agricultural production systems. However, agricultural yields in Africa are far below their potential. One of the challenges leading to low productivity is Africa‘s poor soil quality. Effective soil fertility management is an essential key factor for optimizing agricultural pro...

In recent decades, space-borne hyperspectral sensors have demonstrated significant potential for agricultural monitoring by providing rich spectral information, improved feasibility, and cost-effectiveness compared to multispectral satellite imagery. In this study, we investigated the consistency of two hyperspectral satellite sensors, PRISMA and E...

Accurate and efficient crop maps are essential for decision-makers to improve agricultural monitoring and management, thereby ensuring food security. The integration of advanced artificial intelligence (AI) models with hyperspectral remote sensing data, which provide richer spectral information than multispectral imaging, has proven highly effectiv...

As global food demand increases, farming systems experience heightened pressure to enhance productivity on limited arable land. In Africa, including Morocco, smallholder farms are particularly susceptible to climate variability, soil degradation, and suboptimal farming practices, resulting in yield gaps—the disparity between actual and potential yi...

In the dynamic landscape of modern manufacturing, the pursuit of efficiency, reliability, and optimal performance has prompted the integration of cutting-edge technologies. Among these, digital twins (DT) have emerged as transformative tools, offering a virtual representation of physical processes, systems, and equipment. This paper delves into the...

In minerals processing, the froth flotation is one of the widely used process that separates valuable mineral components from their associated gangue materials. The efficiency of this process relies on several factors, such as feed characteristics, particle size, pulp flow rate, pH, conditioning time, aeration, reagents system and many other affect...

Digitalization is crucial for achieving product quality, cost reduction, and timely delivery in manufacturing. With the rise of Industry 4.0, Digital Twin technology has gained popularity, enabling real-time monitoring, predictive maintenance, process optimization, and assumption testing. Manufacturing Digital Twins utilize digital models to repres...

Safety in underground mining is critically challenged by environmental conditions and the need for rigorous adherence to safety protocols. Draa Sfar, the deepest mine in Morocco, presents extreme conditions that test the effectiveness of Personal Protective Equipment (PPE) compliance. This study addresses the gaps in real-time safety monitoring and...

In this study, we explore the effectiveness of a hybrid modelling approach that seamlessly integrates data-driven techniques, specifically Machine Learning (ML), with physics-based equations in Simulation. In cases where real-world data for industrial processes is insufficient, a simulation tool is employed to generate an extensive dataset of proce...

This study aims to assess the squeezing rock severity at Draa Sfar deep underground mine in Morocco. In fact, this phenomenon is one of the frequent geotechnical issues occurring in deep underground mines, especially those excavated in weak rock formations. Therefore, this study is necessary to evaluate the squeezing potential of pelites, which are...

The control of the froth flotation process in the mineral industry is a challenging task due to its multiple impacting parameters. Accurate and convenient examination of the concentrate grade is a crucial step in realizing effective and real-time control of the flotation process. The goal of this study is to employ image processing techniques and C...

The use of thermal imaging and computer vision has seen a sharp increase in recent years. This paper presents the current state of the art concerning these fields. Thus, a review of research articles studying the combination of these technologies for pattern recognition is established. After presenting an overview of the topic, a bibliometric analy...

The mining industry’s continuous pursuit of sustainable practices and enhanced operational efficiency has led to an increasing interest in leveraging innovative technologies for process monitoring and optimization. This study focuses on the implementation of Convolutional Neural Networks (CNN) for real-time monitoring of differential flotation circ...

Rock mass joint set identification, crucial for geological and geotechnical studies, is often based on stereographic projection. However, the related software programs can eventually present some access limitations. Therefore, with the development of the Artificial Intelligence field and the sharp increase in Machine Learning and Deep Learning appl...

Accurate monitoring of the mineral grades in the flotation froth is crucial for efficient minerals separation in the mining industry. In this study, we propose the use of ConvLSTM, a type of neural network that combines Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks, to create a model that can extract spatial and te...

The goal of this paper is to develop a deep learning model for predicting citrus yield. The data used consists of two sources: (1) field data that includes information on fertilization and phytosanitary treatment products, water quantities used for irrigation, climatic data (temperature, precipitation, humidity, wind speed, and solar radiation), pa...

The ever-increasing global population presents a looming threat to food production. To meet growing food demands while minimizing negative impacts on water and soil, agricultural practices must be altered. To make informed decisions, decision-makers require timely, accurate, and efficient crop maps. Remote sensing-based crop mapping faces numerous...

Beside all the challenges regarding climate change, resources scarcity and quality degradation of deposits, the mining industry is becoming an environment that is constantly under pressure and restrictive. The increasing of raw materials prices, the unstable and high volatile commodity prices, the decreasing ore grades and the rising energy cost ha...

Accurate and timely investigation to concentrate grade in mining industry is a premise of realizing real time and efficient control in a froth flotation process. This study seeks to use image processing and artificial intelligence technologies to predict the elemental composition of minerals in the flotation froth. The online analyzer is a flotatio...

Remote sensing-based crop mapping has continued to grow in economic importance over the last two decades. Given the ever-increasing rate of population growth and the implications of multiplying global food production, the necessity for timely, accurate, and reliable agricultural data is of the utmost importance. When it comes to ensuring high accur...

The overall goal of this study is to define an intelligent system for predicting citrus fruit yield before the harvest period. This system uses a machine learning algorithm trained on historical field data combined with spectral information extracted from satellite images. To this end, we used 5 years of historical data for a Moroccan orchard compo...

Intelligent Transportation Systems (ITS) are the most widely used systems for road traffic management. The vehicle type classification (VTC) is a crucial ITS task due to its capability to gather valuable traffic information. However, designing a performant VTC method is challenging due to the considerable intra-class variation of vehicles. This pap...

Artificial intelligence-based speech recognition systems are already available and capable of recognizing the French language. Still, it is quite time-consuming to compare which one will be effective for an assistant robot. The study aims to select the best French-language speech recognition system with the least error in a real environment. In thi...

Recently, Morocco has started to invest in IoT systems to transform our cities into smart cities that will promote economic growth and make life easier for citizens. One of the most vital addition is intelligent transportation systems which represent the foundation of a smart city. However, the problem often faced in such systems is the recognition...

This paper presents a science mapping approach to analyze thematic evolution of face recognition research. For this reason, different bibliometric tools are combined (performance analysis, science mapping and Co-word analysis) in order to identify the most important, productive and the highest-impact subfields. Moreover, different visualization too...

Moroccan Intelligent Transport System is the first Moroccan system that uses the latest advances in computer vision, machine learning and deep learning techniques to manage Moroccan traffic and road violations. In this paper, we propose a fully automatic approach to Multiple Hypothesis Detection and Tracking (MHDT) for video traffic surveillance. T...

Worldwide, traffic accidents are recognized as one of the leading causes of death. This phenomenon leads to significant daily losses affecting both road users and road authorities. Therefore, the need for effective dynamic road security systems is highly considered. Traffic accident data analysis is one of the promising approaches for improving roa...

The process of phosphate extraction can significantly benefit from the advances in spectral analysis and Artificial Intelligence to reduce the cost of the drilling operation. The ambiguities caused by the apparent similarities between different layers and by the existing mineralogical alterations complexify the delineation of phosphate layers with...

In this paper, we propose a robust real-time vehicle tracking and inter-vehicle distance estimation algorithm based on stereovision. Traffic images are captured by a stereoscopic system installed on the road, and then we detect moving vehicles with the YOLO V3 Deep Neural Network algorithm. Thus, the real-time video goes through an algorithm for st...

Vehicle type classification is a critical functionality in any Intelligent Transportation System (ITS). In this paper, we present a novel two-layers vehicle type classification framework based on the vehicle’s 3D parameters and its local features. This framework is a part of the first Moroccan Video Intelligent Transport System (MOVITS) which aims...

Dans cet article, nous présentons une nouvelle technique pour estimer la vitesse du trafic en utilisant la stéréo-vision. Tout d'abord, des images sont capturées par un système stéréo-scopique installé sur route, puis nous détectons les véhicules en mouvement avec la soustraction de l'arrière plan. Après, une carte de profondeur de la scène est gén...

Ce travail consiste à développer un nouveau algorithme pour un radar d'estimation de vitesse stéréoscopique en utilisant deux caméras. Notre algorithme commence par la détection et le suivi des objets mobiles sur la scène filmée par la première caméra, la deuxième caméra nous permis de constituer un système stéréoscopique qui va servir à calculer l...

Several algorithms have already made to estimate vehicle’s speed using single camera. The main problem is the efficiency of these systems: processing is done on the whole image while moving objects occupy only a specific part. This work aims to present a technique of speed estimation based on one pixel’s width line processing. This line image can b...

The aim of this study was to validate/calibrate two tools to be able to reliably measure/predict warpage at ambient temperature, especially for ball grid array (BGA) electronic packages. The tools used in this study were a high-precision microscope and a finite-element model. First, the authors calibrated the microscope by comparing the obtained re...

A massively parallel machine based on Serial RapidIO (SRIO) interconnect is presented in this paper. The proposed machine consists of multi digital signal processors (multi-DSPs) and multi-cores in one DSP. A core is the basic processing element and the SRIO is the inter-processors communication bus. This paper presents several cases studies of tra...

Machine vision algorithms require high-computing power. A high performance parallel system has been proposed in this paper by implementing a road traffic radar video processing chain in real-time on a new embedded architecture. The proposed machine consists of the Digital Signal Processor (DSP) 66AK2H12 from Texas Instruments (TI). The goal of this...

This work is part of developing a new type of radars which is based on stereoscopic effect obtained by using two cameras. The main work is to develop an algorithm for speed estimation. We begin by detecting motions and tracking vehicles in order to identify the vehicle in the next frame. Stereoscopic pictures allow us to calculate the distance from...

Pulse-Doppler radars require high-computing power. A massively parallel machine has been developed in this paper to implement a Pulse-Doppler radar signal processing chain in real-time fashion. The proposed machine consists of two C6678 digital signal processors (DSPs), each with eight DSP cores, interconnected with Serial RapidIO (SRIO) bus. In th...

Le convertisseur automatique de débit d'images est un bloc électronique écrit en langage de programmation hardware qui est le vhdl. Ce bloc vhdl permet la gestion automatique d'un flux vidéo provenant d'une source externe (ex caméra numérique). Le rôle du bloc est d'adapter le flux d'images entrant (provenant de la caméra) à la bande passante de l'...

Serial RapidIO is a high-performance, packet-switched that was developed to address the embedded industry's need in term of faster bus speeds, increased bandwidth and reliability. Serial RapidIO allows chip-to-chip and onboard communications. In this paper, we present experimental results on performances optimizations of the Serial RapidIO intercon...

Le système intitulé « carte électronique multi caméra et multifonctions >> est une carte électronique qui sert à l'acquisition parallèle de 4 flux vidéo provenant de 4 cameras numériques externes. Les vidéos reçues ont la qualité HD avec la technologie 3d et débit d'images supérieur à 3ofps. Le système héberge une puce de type ASIC de la catégorie...

This communication addresses the problem of the blur introduced by the out-of-focus defect. We present a new image deblurring technique: it combines a new blur measurement method with the deconvolution algorithm. The proposed technique consists of two steps. The first one allows to estimate the point-spread-function of the optical system by the ite...

The proposed dielectric resonator antenna (DRA) structure has a very low profile, a very small size, 10 × 10 × 2:5mm 3 DRA and 10 × 35mm 2 substrate size, and low permittivity constant (10.2). The simulated impedance bandwidth, achieved is about 73%, from 5.59 GHz to 12 GHz. The considered DRA radiation pattern is quasi-omni directional and has a s...

In this paper, a new model and compensation scheme of quadrature imbalance in analog I/Q OFDM transceivers is presented. Classically, the effect of I/Q imbalance is modeled by a crosstalk between pairs of symmetrical OFDM sub-carriers. We show that this model is not valid when the carrier frequency offset is compensated after the source of I/Q mism...

We outline the necessity of regularizing a deconvolution procedure, in the general framework of the inverse problems involved in astronomy. We show that this regularization depends in particular on a signal-to-noise ratio criterion. We concentrate on the application of the soft-thresholding statistical method for estimating the noise. We give the c...