http://repository.enp.edu.dz/jspui/handle/123456789/145 2026-04-07T05:12:43Z http://repository.enp.edu.dz/jspui/handle/123456789/11243 Plant leaves disease severity stimation Abid, Wissam Smart agriculture aims to improve crop monitoring through automated and accurate analysis of plant health. A critical task in this domain is disease severity estimation, which focuses on identifying the progression stages of plant infections. In this work, we propose a deep learning-based solution using two transformer architectures: Vision Transformer (ViT) and Swin Transformer. These models are implemented, evaluated, and combined into a novel architecture that leverages ViTs global attention and Swins hierarchical local attention for fine-grained severity classification. The models are trained on Wheat Yellow Rust dataset, which includes six severity stages. Finally, results show that the combined model outperforms individual baselines, providing an effective solution for automated severity estimation. Mémoire de Projet de Fin d’Études : Electronique : Alger, École Nationale Polytechnique : 2025 2025-01-01T00:00:00Z http://repository.enp.edu.dz/jspui/handle/123456789/11240 Development of an autonomous 6DOF robotic arm using machine learning Belkhiri, Djamel Ibrahim; Benarab, Adel This thesis presents the development of a 6-DOF autonomous collaborative robotic arm, covering mechanical design, kinematic & dynamic analysis, 3D printing, and full electrical system integration. The robot is controlled via ROS and Robodk for simulation and motion planning. Autonomy is achieved through supervised learning, reinforcement learning, and ArUco marker-based pose estimation. The final system demonstrates a robust and flexible autonomous robotic arm capable of performing industrial tasks. Mémoire de Projet de Fin d’Études : Electronique : Alger, École Nationale Polytechnique : 2025 2025-01-01T00:00:00Z http://repository.enp.edu.dz/jspui/handle/123456789/11235 Sound source localization and tracking : real life application using UMA-16 Bouznad, Tarek This thesis addresses two major challenges in acoustic signal processing: motion parameter estimation using the Doppler effect, and sound source localization with microphone arrays. The first part explores how the instantaneous frequency (IF) shift induced by the Doppler effect enables the estimation of a moving source’s velocity, altitude, and emission frequency using a single microphone, through a closed-form solution validated by simulation. The second part focuses on speaker localization and separation using spatial filtering methods (SRP-PHAT, MVDR, LCMV). A real-time system is implemented with a MiniDSP UMA-16 microphone array and a camera for visual projection. Mémoire de Projet de Fin d’Études : Electronique : Alger, École Nationale Polytechnique : 2025 2025-01-01T00:00:00Z http://repository.enp.edu.dz/jspui/handle/123456789/11232 Multimodal neurophysiological signals analysis for stress assessment Boulefaat, Israa; Cherfouhi, Mohamed Abdelhadi This project investigates the use of neurophysiological signals, specifically EEG, ECG, and PPG, for stress assessment in 23 participants performing various tasks, with corresponding stress levels recorded for each activity. The signals are segmented and filtered, then converted into images using two distinct techniques: Visibility Graph and Gramian Angular Field Image Representations. This multimodal approach enables the integration of diverse and complementary information from different physiological sources. Feature extraction is subsequently performed using two complementary strategies: Wavelet Packet Transform combined with Zernike and Hu Moments, and Semi-Classical Signal Analysis (SCSA). Once the full processing pipeline is completed, a supervised machine learning model is trained using the stress labels in order to evaluate and compare the performance of each feature extraction method. For each signal type, the most effective strategy is selected, and their outputs are then fused to enhance the overall performance of the stress assessment system by leveraging the benefits of multimodality. Mémoire de Projet de Fin d’Études : Electronique : Alger, École Nationale Polytechnique : 2025 2025-01-01T00:00:00Z