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Automatic Face Expression Neutralisation and Posture Correction via 3D Contrastive Learning 27

Automatic Face Expression Neutralisation and Posture Correct...

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27th International Conference on Knowledge Based and Intelligent Information and Engineering Sytems, KES 2023

作者： Wiem, Grina Ali, Douik University of Sousse Networked Objects Control and Communication Systems Laboratory National School of Engineers of Sousse Sousse Technology Center University of Monastir National Engineering School of Monastir Sahloul Belt Road 4054 Rue Ibn Jazzar Monastir5035 Tunisia University of Sousse Networked Objects Control and Communication Systems Laboratory National School of Engineers of Sousse Sousse Technology Center Sahloul Belt Road 4054 Tunisia

The performance of recognition systems can be significantly affected by various factors, with facial expression poses and lighting changes being the main confounding factors. In order to minimize their impact, we propose an intriguing method in this study that enables the generation of high-quality images specifically tailored to the target domain. Our objective is to utilize disentangled representation to effectively model the decomposition of data variations and generate neutral facial expression images with frontal posture and adaptive illumination. To achieve this, we incorporate 3D priors in the adversarial learning during the training process, simulating the generation of an analytical 3D face deformation as well as rendering operations. Additionally, we employ contrastive learning to control the disentanglement of the generated faces while preserving the essential properties of facial features. This technique enables us to learn an embedding space in which similar data samples are represented closely, while distinct samples are kept far apart from each other. Furthermore, we conduct an analysis of the learned latent space and introduce several other significant properties that enhance the reinforcement of factor disentanglement. These properties include an imitation learning algorithm, which facilitates the acquisition of meaningful patterns and characteristics. © 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0)

关键词： 3D contrastive learning disentanglement expression neutralization generative adversarial network

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control of the chaotic phenomenon in robot path using differential flatness 15

Control of the chaotic phenomenon in robot path using differ...

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15th International Conference on Informatics in control, Automation and Robotics, ICINCO 2018

作者： Nasr, Salah Abadi, Amine Bouallegue, Kais Mekki, Hassen Laboratory of Networked Objects Control and Communication Systems National Engineering School of Sousse University of Sousse Tunisia Department of Electrical Engineering Higher Institute of Applied Sciences and Technology of Sousse Tunisia

ISBN: (纸本)9789897583216

This paper deals with the complex chaotic behavior that can appear in the dynamic trajectory of a mobile robot, when the robot is broken or partly damaged. However, a flatness-based controller is designed to ensure the trajectory planning and tracking. Different mathematical tools have been used such as the flatness control technique and non linear chaotic systems. The simulation results for the kinematic controller are presented to demonstrate the effectiveness of this approach. Copyright © 2018 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

关键词： Mobile robots

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Chaos engineering and control in mobile robotics applications 15

Chaos engineering and control in mobile robotics application...

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15th International Conference on Informatics in control, Automation and Robotics, ICINCO 2018

作者： Nasr, Salah Abadi, Amine Bouallegue, Kais Mekki, Hassen Networked Objects Control and Communication Systems-Laboratory National Engineering School of Sousse University of Sousse Tunisia Department of Electrical Engineering Higher Institute of Applied Sciences and Technology of Sousse Tunisia

ISBN: (纸本)9789897583216

This article briefly summarizes the theory of chaos and its applications. Firstly, we begin by describing chaos as an aperiodic bounded deterministic motion, which is sensitive to initial states and therefore unpredictable after a certain time. Then, fundamental tools of the chaos theory, used for identifying and quantifying chaotic dynamics, are shared. The paper covers a main numerical approach to identify chaos such as the Lyapunov exponents. Many important applications of chaos in several areas such as chaos in electrical and electronic engineering and chaos applications in robotics have been presented. An analysis of the reviewed publications is presented and a brief survey is reported as well. Copyright © 2018 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

关键词： Chaos control

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Experimental validation of flatness control for path planning and tracking for a quadrotor

Experimental validation of flatness control for path plannin...

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2017 International Conference on Engineering and MIS, ICEMIS 2017

作者： Chelly, Nizar Mekki, Hassen Ibrahim, Anis Belhadj Networked Objects Control Communication Systems Lab National School of Engineering Sousse Sousse University Tunisia National School of Engineering Sousse Sousse University Tunisia

ISBN: (纸本)9781509067787

In this paper, we investigates the problem of planning and tracking trajectory for a non linear system which is the quadrotor using the flatness theory. The proposed flatness algorithm is real time implemented. The Experimental results using this solution validate the design control along a pre defined trajectory as well as the response of the AR Drone under disturbances is evaluated. © 2017 IEEE.

关键词： Nonlinear systems

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Systemized software hardware partitioning algorithm for system on programmable chip to minimize logic power

Systemized software hardware partitioning algorithm for syst...

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2017 International Conference on Engineering and MIS, ICEMIS 2017

作者： Jemai, Mehdi Ben Haj Hassine, Siwar Mtibaa, Abdellatif Ouni, Bouraoui Laboratory of Electronic and Microelectronic National Engineering School of Monastir University of Monastir Monastir5000 Tunisia Networked Objects Control and Communication Systems Laboratory National Engineering School of Sousse University of Sousse Sousse4023 Tunisia

ISBN: (纸本)9781509067787

To reduce the power consumption, in the literature, most works have focused in the field of batteries. However despite the progress made in this area, it is difficult to increase the battery capacity without increasing the weight, volume and price. To overcome such problems, in this paper we present a new approach based on hardware-software partitioning to reduce power consumption. In fact, in this paper we aim to solve the following issue: Given a control data flow graph a System on a Programmable Chip circuit;find a possible hardware-software partitioning of the graph on the System on a Programmable Chip in order to minimize the logic power and satisfying a temporal constraint. © 2017 IEEE.

关键词： Electric power utilization

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Optimal trajectory generation and flatness tracking control for a mobile robot 18

Optimal trajectory generation and flatness tracking control ...

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18th International Conference on Sciences and Techniques of Automatic control and Computer Engineering, STA 2017

作者： Abadi, Amine Mekki, Hassen Ben Hadj Brahim, Anis El Amraoui, Adnen Ramdani, Nacim National Engineering School of Sousse University of Sousse Networked Objects Control and Communication Systems Laboratory Tunisia Univ. Orléans INSA CVL PRISME EA 4229 OrleansF45072 France

ISBN: (纸本)9781538610848

This work proposes an optimal trajectory generation and a controller design for a mobile robot. The objective consists of creating a new performance guidance module for the mobile robot in a closed environment. The reference trajectory can be calculated by solving an optimization problem. The properties of the differential flatness, the B-spline and the direct collocation method are exploited to convert the constrained optimization problem into a nonlinear programming one that can be easily resolved by a classic solver. After that, the obtained optimal reference trajectory is used in the kinematic mobile robot model. A flatness-based controller is designed to ensure the trajectory tracking. The numerical simulations are done in order to evaluate the proposed optimal trajectory generation approach and the tracking strategy. © 2017 IEEE.

关键词： Mobile robots

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An FPGA-SoC based Hardware Acceleration of Convolutional Neural Networks 9

An FPGA-SoC based Hardware Acceleration of Convolutional Neu...

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9th IEEE International Conference on Sciences of Electronics, Technologies of Information and Telecommunications, SETIT 2022

作者： Bouaafia, Soulef Messaoud, Seifeddine Khemiri, Randa Sayadi, Fatma Ezahra Monastir University Lab. Electronics and Microelectronics Faculty of Sciences of Monastir Monastir Tunisia Sousse University Lab. Networked Objects Control and Communication Systems National Engineering School of Sousse Sousse Tunisia

ISBN: (数字)9781728184425

ISBN: (纸本)9781728184425

Deep learning has evolved as a discipline that has demonstrated its capacity and usefulness in tackling complicated learning issues as a result of recent improvements in digital technology and the availability of authentic data. Convolutional neural networks (CNNs) in particular have demonstrated their usefulness in image processing and computer vision applications. They do, however, need heavy CPU operations and memory bandwidth, which prevents general-purpose CPUs from attaining desirable performance levels. To boost CNN throughput, hardware accelerators such as application-specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), and graphics processing units (GPUs) have been deployed. FPGAs, in particular, have lately been used to accelerate the development of deep learning networks due to their ability to optimize parallelism and power efficiency. Based on hardware-software architecture, this research provides a CNN acceleration model for video compression applications. Vivado High Level Synthesis is used to accelerate the CNN model in order to develop Intellectual Property (IP) cores. © 2022 IEEE.

关键词： Convolutional neural networks

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Embracing the Future: The Evolution of Flexible Reconfigurable Manufacturing systems

Embracing the Future: The Evolution of Flexible Reconfigurab...

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systems, Advanced Technologies and Knowledge (ISSATK), International Symposium of

作者： Salah Hammedi Jalloul Elmeliani Lotfi Nabli National School of Engineers of Monastir Networked Objects Control and Communication Systems (NOCCS) ENISo University of Sousse Tunisia National Engineering School of Bizerte Networked Objects Control and Communication Systems (NOCCS) ENISo University of Sousse Tunisia

ISBN: (数字)9798331540173

ISBN: (纸本)9798331540180

Flexible Reconfigurable Manufacturing systems (FRMS) are a radical approach to modern manufacturing, focusing on adaptability and efficiency to respond to dynamic market demands. The fundamental principles and advantages of FRMS are discussed in this article. These systems offer a versatile solution to traditional, inflexible manufacturing setups thanks to their modularity, automation, reconfigurability and data-driven decision-making. The key benefits include the ability to adapt to changing production requirements, cost efficiency, improved product quality, and resource optimization. FRMS are found in various industries, such as automotive, electronics, aerospace, and pharmaceuticals, and they meet the needs of customization, precision, and rapid production shifts. FRMS’s future looks promising, as emerging trends like AI integration, sustainability, customization, and interconnectivity are poised to further enhance their capabilities. Manufacturers can excel in an ever-evolving industrial landscape thanks to FRMS’s position in meeting the challenges of an increasingly dynamic global market as they continue to evolve.

关键词： Adaptation models Scalability Decision making Market research Aerodynamics Software systems Security Vehicle dynamics Sustainable development Manufacturing systems

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Local saliency estimation and global homogeneity refinement for video saliency detection 11th

Local saliency estimation and global homogeneity refinement ...

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11th International KES Conference on Intelligent Interactive Multimedia: systems and Services, KES-IIMSS 2018

作者： Kalboussi, Rahma Abdellaoui, Mehrez Douik, Ali Networked Objects Control and Communication Systems Laboratory Pôle technologique de Sousse Route de Ceinture Sahloul Sousse4054 Tunisia University of Sousse Sousse Tunisia Higher Institute of Computer Sciences and Communications Technology Hammam SousseSousse Tunisia

ISBN: (纸本)9783319922300

Saliency detection aims to segment the object of interest from the rest of the scene. While there has been a big number of saliency detection methods in still images, video saliency is in its early stages. In this paper, we propose a two stages video saliency detection method using local saliency estimation and global homogeneity refinement. Starting from a patch, the problem of saliency detection is modeled as a growing region which starts from a patch with high saliency information to the background. Local saliency is measured by combining spatial priors presented by local surrounding contrast with temporal information issued from the motion estimation feature. Temporal and spatial information are fused and then used to label each patch as foreground and background patches and produce the final saliency maps. Finally, Global homogeneity refinement is used to refine the saliency results by evaluating the foreground and background probabilities ratio propagated from the patches. Experiments have proved that the proposed method outperforms state-of-the-art methods over two benchmark datasets. © Springer International Publishing AG, part of Springer Nature 2019.

关键词： Motion estimation

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FFGAN: An Auto-supervised Approach for Frontal Face Generation Via Disentangled Contrastive Learning 28th

FFGAN: An Auto-supervised Approach for Frontal Face Generati...

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28th International Conference on Knowledge Based and Intelligent information and Engineering systems, KES 2024

作者： Wiem, Grina Ali, Douik National Engineering School of Monastir University of Monastir Rue Ibn Jazzar Monastir5035 Tunisia Networked Objects Control and Communication Systems Laboratory Sousse Technology Centre National School of Engineers of Sousse University of Sousse Sahloul Belt Road Sousse4054 Tunisia

This work proposes a novel generative model, FF-GAN (Frontal Face Generative Adversarial Network), for generating high-quality and diverse frontal faces. FF-GAN utilizes contrastive learning to effectively learn the underlying representation of frontal faces from unlabeled image datasets. This approach allows the model to capture the essential characteristics of frontal faces without the need for explicit pose annotations. We evaluate the performance of FF-GAN using established metrics like FID (Fréchet Inception Distance), IS (Inception Score), and SSIM (Structural Similarity Index Measure). The results demonstrate that FF-GAN achieves superior performance compared to existing methods, generating highly realistic and visually appealing frontal faces with exceptional structural coherence. This research contributes to the field of facial image generation by introducing an effective unsupervised learning approach based on contrastive learning for generating high-quality frontal faces. © 2024 The Authors.

关键词： Contrastive Learning

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