Ouahab Kadri received, his Habilitation from the Department of Industrial Engineering, University of Batna, Algeria, in 2018. He received, his PhD from the Department of Industrial Engineering, University of Batna, in 2013. He is currently an Assistant Professor in the Department of Computer Science at the University of Batna2, Algeria. He was an Assistant Professor in the Department of Mathematics and Computer Science at the University of Khenchela, Algeria. He received his Magister degree from Department of Computer Science, University of Batna, Algeria. He has published five books and over 20 papers. His current research interests include evolutionary computation and artificial intelligence.
EDUCATION
Habilitation en génie industriel au Laboratoire d’Automatique et Productique à l’université de BATNA
RESEARCH INTERESTS
Support Vector Machine
Ant Colony Optimization
Evolutionary Computation
Optimization
Computational Intelligence
Applied Artificial Intelligence
Neural Networks and Artificial Intelligence
Classification
Feature Extraction
Feature Selection
A Highly Effective Deep Learning Tool for Identifying Plant Leaves Adel Abdelhadi, Ouahab Kadri Agris on Line Papers in Economics and Informatics, 2026 This work addresses pattern recognition in the agronomic domain, with a particular emphasis on identifying plant leaves using an adaptive neural network technique. We introduce a tool designed for two primary groups: botany researchers and a broader range of scientists applying it to plant identification and classification. We delve into the capabilities of Deep Learning, focusing on generalization abilities that enable accurate predictions on unseen data, which is essential for handling the variation in leaf shapes, sizes, and structures across species. The implementation details of these neural networks are described, including data preprocessing, network architecture design, training strategies, and evaluation techniques to ensure robustness and reliability in real-world applications.
Optimizing Milk Pasteurization Diagnosis Through Deep Q-Networks and Digital Twin Technology Ouahab Kadri, Adel Abdelhadi International Journal of Web Services Research, 2024 Industrial diagnostic systems play an important role in food manufacturing by ensuring rapid detection of defective components and precise identification of systemic dysfunction. This article proposes a diagnostic model for the pasteurization process to enhance dairy production systems. The authors found that, when a breakdown occurs, the acquisition system stops providing necessary data for diagnostics. To solve this problem, the authors used digital twin (DT) engineering to generate missing values and build a learning model based on reinforcement learning (RL). The effectiveness of this approach was validated through implementation at Aures Batna Dairy, a prominent player in Algeria's dairy industry. Experiments demonstrated the superior efficiency of this method; its precision surpassed that of traditional data imputation techniques by a significant margin.
Enhanced Energy Efficiency in Visual Sensor Networks through ROI-Based Compression Techniques in Wildlife Surveillance Oussama Hadji, Moufida Maimour, Ouahab Kadri, Abderrezak Benyahia, Eric Rondeau 2024 12th International Conference on Systems and Control ICSC 2024, 2024 This paper presents an application of a Region of Interest(ROI)-based compression technique designed to enhance the energy efficiency of visual sensor networks used in wildlife monitoring. By focusing on compressing only the most critical regions within each video frame, the proposed method significantly reduces data volume, leading to substantial energy savings during both compression and transmission stages. The integration of LoRaWAN technology further optimizes energy consumption by providing low-power, long-range communication capabilities. Experimental results demonstrate a compression ratio of 4:1, achieving overall energy savings of approximately 38% for short-range and 40% for long-range transmission compared to traditional non-ROI methods. Despite a slight reduction in image quality, the visual integrity remains acceptable for effective wildlife monitoring, and the method improves transmission success rates over varying distances. These findings highlight the potential of ROI-based compression to extend the operational lifespan of sensor nodes, offering a viable and sustainable solution for long-term environmental monitoring.
TRANSFORMATION OF 2D IMAGES INTO 3D BY THE DEEP-LEARNING Academic Journal of Manufacturing Engineering, 2023
Faulty Detection System Based on SPC and Machine Learning Techniques Mohamed Elamine Benrabah, Ouahab Kadri, Kinza Nadia Mouss, Abdelghani Lakhdari Revue D Intelligence Artificielle, 2022 Starting from a worrying observation, that companies have difficulties controlling the anomalies of their manufacturing processes, in order to have a better control over them, we have realized a case study on the practical data of the Fertial Complex to analyze the main parameters of the ammonia neutralization by nitric acid process. This article proposes a precise diagnostic of this process to detect dysfunction problems affecting the final product. We start with a general diagnosis of the process using the SPC method, this approach is considered an excellent way to monitor and improve the product quality and provides very useful observations that allowed us to detect the parameters that suffer from problems affecting the quality. After the discovery of the parameters incapable to produce the quality required by the standards, we applies two machine learning technologies dedicated to the type of data of these parameters for detected the anomaly, the first technique called The kernel connectivity-based outlier factor (COF) algorithm consists in recording for each object the degree of being an outlier, the second technique called the Isolation Forest, its principle is to establish a forest to facilitate the calculation and description. The results obtained were compared in order to choose which is the best algorithm to monitor and detect the problems of these parameters, we find that the COF method is more efficient than the isolation forest which leads us to rely on this technology in this kind of process in order to avoid passing a bad quality to the customer in future.
Tifinagh Handwriting Character Recognition Using a CNN Provided as a Web Service Ouahab Kadri, Abderrezak Benyahia, Adel Abdelhadi International Journal of Cloud Applications and Computing, 2022 Many cloud providers offer very high precision services to exploit Optical Character Recognition (OCR). However, there is no provider offers Tifinagh Optical Character Recognition (OCR) as Web Services. Several works have been proposed to build powerful Tifinagh OCR. Unfortunately, there is no one developed as a Web Service. In this paper, we present a new architecture of Tifinagh Handwriting Recognition as a web service based on a deep learning model via Google Colab. For the implementation of our proposal, we used the new version of the TensorFlow library and a very large database of Tifinagh characters composed of 60,000 images from the Mohammed Vth University in Rabat. Experimental results show that the TensorFlow library based on a Tensor processing unit constitutes a very promising framework for developing fast and very precise Tifinagh OCR web services. The results show that our method based on convolutional neural network outperforms existing methods based on support vector machines and extreme learning machine.
Hybrid multi-agent and immune algorithm approach to hybrid flow shops scheduling with SDST Academic Journal of Manufacturing Engineering, 2020
Identification and detection of the process fault in a cement rotary kiln by extreme learning machine and ant colony optimization Academic Journal of Manufacturing Engineering, 2017
An efficient hybrid approach based on SVM and binary ACO for feature selection 10th International Conference on Modeling and Applied Simulation Mas 2011 Held at the International Mediterranean and Latin American Modeling Multiconference I3m 2011, 2011
A hybrid feature subset selection approach based on SVM and binary ACO. Application to industrial diagnosis World Academy of Science Engineering and Technology, 2010
RECENT SCHOLAR PUBLICATIONS
Vid-Sim: Modeling and analysis of video encoding and transmission in wireless sensor-based surveillance O Hadji, M Maimour, E Rondeau, O Kadri, A Benyahia SoftwareX 34, 102658 , 2026 2026
A Highly Effective Deep Learning Tool for Identifying Plant Leaves A Abdelhadi, O Kadri AGRIS on-line Papers in Economics and Informatics 17 (4), 3-9 , 2025 2025
Enhanced Network Security Through Optimized Feature Subset Selection Using GTO Algorithm A Benyahia, O Kadri, M Hamouma, A Abdelhadi Journal of Communications Software and Systems 21 (4), 512-520 , 2025 2025 Citations: 1
FAULT DIAGNOSIS BASED ON NATURE-INSPIRED FEATURE SELECTION METHODS. A ABDELHADI, O KADRI, MT Eddine SEDDIK Academic Journal of Manufacturing Engineering 23 (3) , 2025 2025
Sound-Based Bird Localization Using Lightweight Convolutional Neural Networks and Internet of Things C Bouarouguene, M Maimour, O Kadri, A Benyahia, E Rondeau 1st International Conference on Green Engineering , 2025 2025 Citations: 4
EcoWatch: Region of interest-based multi-quantization resource-efficient framework for migratory bird surveillance using wireless sensor networks and environmental context … O Hadji, M Maimour, A Benyahia, O Kadri, E Rondeau Computers and Electrical Engineering 123, 110076 , 2025 2025 Citations: 6
Fault Detection Using Hotelling T² Chart and Artificial Neural Networks ME BENRABAH, O KADRI, A LAKHDARI, N BENHASSINE 2025
Enhanced Energy Efficiency in Visual Sensor Networks through ROI-Based Compression Techniques in Wildlife Surveillance O Hadji, M Maimour, O Kadri, A Benyahia, E Rondeau 2024 12th International Conference on Systems and Control (ICSC), 395-400 , 2024 2024 Citations: 4
Enhancing epidemic management: agent-based simulation and remote diagnosis DE Abdelaziz, O Kadri Brazilian Journal of Technology 7 (2), e70355 , 2024 2024
Optimizing Milk Pasteurization Diagnosis Through Deep Q-Networks and Digital Twin Technology O Kadri, A Abdelhadi International Journal of Web Services Research (IJWSR) 21 (1), 1-22 , 2024 2024 Citations: 2
A New Operator that Combines Artificial Immune Systems and Multi-Agent Systems for Addressing Flow Shop Scheduling Problems A Abdelhadi, O Kadri Brazilian Journal of Technology 7 (4), e76226 , 2024 2024 Citations: 2
Dnn inference splitting and offloading in the internet of things: A survey C Bouarouguene, M Maimour, O Kadri, E Rondeau, A Benyahia 1er Congrès annuel de la Société d’Automatique de Génie Industriel et de … , 2023 2023 Citations: 3
Proposed system for efficient wildlife monitoring using wsn and image processing O Hadji, A Benyahia, M Maimour, E Rondeau, O Kadri 1er Congrès annuel de la Société d’Automatique de Génie Industriel et de … , 2023 2023 Citations: 3
TRANSFORMATION OF 2D IMAGES INTO 3D BY THE DEEPLEARNING. A ABDELHADI, O KADRI Academic Journal of Manufacturing Engineering 21 (2) , 2023 2023 Citations: 1
Faulty Detection System Based on SPC and Machine Learning Techniques. ME Benrabah, O Kadri, KN Mouss, A Lakhdari Revue d'Intelligence Artificielle 36 (6) , 2022 2022 Citations: 2
Region of interest and redundancy problem in migratory birds wild life surveillance O Hadji, O Kadri, M Maimour, E Rondeau, A Benyahia 2022 International Conference on Advanced Aspects of Software Engineering … , 2022 2022 Citations: 16
Imputation as service using support vector regression: Application to a photovoltaic system in Algeria MTE Seddik, O Kadri, MR Abdessemed 1st National Conference of Materials sciences And Engineering,(MSE'22) , 2022 2022 Citations: 1
Tifinagh Handwriting Character Recognition Using a CNN Provided as a Web Service K Ouahab, B Abderrezak, A Adel International Journal of Cloud Applications and Computing (IJCAC) 12 (1), 1-17 , 2022 2022 Citations: 21
Detection of flooding attack on obs network using ant colony optimization and machine learning M Takieddine Seddik, O Kadri, C Bouarouguene, H Brahimi Computación y Sistemas 25 (2), 423-433 , 2021 2021 Citations: 6
Aircraft engines remaining useful life prediction with an adaptive denoising online sequential extreme learning machine T Berghout, LH Mouss, O Kadri, L Saïdi, M Benbouzid Engineering Applications of Artificial Intelligence 96, 103936 , 2020 2020 Citations: 120
MOST CITED SCHOLAR PUBLICATIONS
Aircraft engines remaining useful life prediction with an adaptive denoising online sequential extreme learning machine T Berghout, LH Mouss, O Kadri, L Saïdi, M Benbouzid Engineering Applications of Artificial Intelligence 96, 103936 , 2020 2020 Citations: 120
Fault diagnosis of rotary kiln using SVM and binary ACO O Kadri, LH Mouss, MD Mouss Journal of mechanical science and technology 26 (2), 601-608 , 2012 2012 Citations: 63
Aircraft engines remaining useful life prediction with an improved online sequential extreme learning machine T Berghout, LH Mouss, O Kadri, L Saïdi, M Benbouzid Applied Sciences 10 (3), 1062 , 2020 2020 Citations: 49
Tifinagh Handwriting Character Recognition Using a CNN Provided as a Web Service K Ouahab, B Abderrezak, A Adel International Journal of Cloud Applications and Computing (IJCAC) 12 (1), 1-17 , 2022 2022 Citations: 21
Region of interest and redundancy problem in migratory birds wild life surveillance O Hadji, O Kadri, M Maimour, E Rondeau, A Benyahia 2022 International Conference on Advanced Aspects of Software Engineering … , 2022 2022 Citations: 16
Electrical faults detection for the intelligent diagnosis of a photovoltaic generator LH MOUSS Journal of Electrical Engineering 14 (1), 8-8 , 2014 2014 Citations: 15
Identification and detection of the process fault in a cement rotary kiln by extreme learning machine and ant colony optimization O KADRI, LH MOUSS Academic Journal of Manufacturing Engineering 15 (2) , 2017 2017 Citations: 12
EcoWatch: Region of interest-based multi-quantization resource-efficient framework for migratory bird surveillance using wireless sensor networks and environmental context … O Hadji, M Maimour, A Benyahia, O Kadri, E Rondeau Computers and Electrical Engineering 123, 110076 , 2025 2025 Citations: 6
Detection of flooding attack on obs network using ant colony optimization and machine learning M Takieddine Seddik, O Kadri, C Bouarouguene, H Brahimi Computación y Sistemas 25 (2), 423-433 , 2021 2021 Citations: 6
Regularized length changeable extreme learning machine with incremental learning enhancements for remaining useful life prediction of aircraft engines T BERGHOUT, LH MOUSS, O KADRI, N HADJIDJ 2020 1st International Conference on Communications, Control Systems and … , 2020 2020 Citations: 5
Sound-Based Bird Localization Using Lightweight Convolutional Neural Networks and Internet of Things C Bouarouguene, M Maimour, O Kadri, A Benyahia, E Rondeau 1st International Conference on Green Engineering , 2025 2025 Citations: 4
Enhanced Energy Efficiency in Visual Sensor Networks through ROI-Based Compression Techniques in Wildlife Surveillance O Hadji, M Maimour, O Kadri, A Benyahia, E Rondeau 2024 12th International Conference on Systems and Control (ICSC), 395-400 , 2024 2024 Citations: 4
Fault prognosis by temporal neuro-fuzzy systems: application for manufacturing systems R Mahdaoui, LH Mouss, O Kadri Proceedings of IEEE SETIT, Sousse, Tunisia, 1-6 , 2012 2012 Citations: 4
La Surveillance Industriel Dynamique par les Systèmes Neuro-Flous Temporels : Application à un système de Production M Rafik, M Hayet, C Ouahiba, K Ouahab, H Hichem International Conference: Sciences of Electronic, Technologies of … , 2009 2009 Citations: 4
Dnn inference splitting and offloading in the internet of things: A survey C Bouarouguene, M Maimour, O Kadri, E Rondeau, A Benyahia 1er Congrès annuel de la Société d’Automatique de Génie Industriel et de … , 2023 2023 Citations: 3
Proposed system for efficient wildlife monitoring using wsn and image processing O Hadji, A Benyahia, M Maimour, E Rondeau, O Kadri 1er Congrès annuel de la Société d’Automatique de Génie Industriel et de … , 2023 2023 Citations: 3
HYBRID MULTI-AGENT AND IMMUNE ALGORITHM APPROACH TO HYBRID FLOW SHOPS SCHEDULING WITH SDST. A ABDELHADI, LH MOUSS, O KADRI Academic Journal of Manufacturing Engineering 18 (3) , 2020 2020 Citations: 3
Reconnaissance des Formes par SVM pour le Diagnostic du Système de Pasteurisation d’une Usine de Lait O Kadri, LH Mouss, MD Mouss, A Abdelhadi Revue des Sciences et de la Technologie-RST-4, 35-52 , 2013 2013 Citations: 3
Optimizing Milk Pasteurization Diagnosis Through Deep Q-Networks and Digital Twin Technology O Kadri, A Abdelhadi International Journal of Web Services Research (IJWSR) 21 (1), 1-22 , 2024 2024 Citations: 2
A New Operator that Combines Artificial Immune Systems and Multi-Agent Systems for Addressing Flow Shop Scheduling Problems A Abdelhadi, O Kadri Brazilian Journal of Technology 7 (4), e76226 , 2024 2024 Citations: 2
