Publications
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Synthetic Data-Driven Augmentation for Precise 6-DoF Pose Estimation of Building Components in Automated Facility Inspections
This paper tackles the challenge of automating facility inspections by detecting building components, estimating their six-degree-of-freedom (6-DoF) poses (position and orienta tion), and comparing these estimations to Building Information Modeling (BIM) ground truth data. Vision based Deep learn ing methods offer promising results in pose estimation. They rely heavily on large annotated image datasets for […]
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Evaluating Robustness of 3D Gaussian Splatting–Based 6D Camera Pose Refinement Under Degraded Conditions for Lightly Textured Industrial Synthetic Objects
In this paper, 6D camera pose refinement is explored using 3D Gaussian Splatting (3DGS) on lightly textured industrial object datasets. The study employs datasets generated with Unity 3D rendering software, featuring objects such as a bicycle, MiR robot, Tiago robot, and UR robotic arm, each captured with ground-truth intrinsic and extrinsic camera parameters. A 3DGS […]
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Attention Makes HVAC Control More Efficient
Heating, ventilation, and air-conditioning (HVAC) systems account for around 16.4% of global final energy consumption and about 14% of global operational CO2 emissions. Controlling them is a partially observable, sequential decision problem: relying solely on instantaneous sensor readings as inputs overlooks the full sequence of past conditions that shape future dynamics. To tackle this challenge […]
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L’innovation juridique à la croisée du droit et de l’innovation : réflexions sur un champ émergent
L’innovation et le droit sont deux domaines étroitement liés, s’influençant mutuellement dès lors qu’il s’agit de réguler, protéger et encourager la création de nouvelles idées, normes juridiques, produits, services ou technologies. S’inscrivant dans le prolongement de l’approche Law & Management, l’innovation juridique constitue un champ de recherche émergent qui tente d’appréhender les influences réciproques entre […]
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Chloé Leduque (2024), Le droit des contrats à l’épreuve de l’économie de partage, Paris, Larcier, 804 p.
Recension d’ouvrage de Chloé Leduque (2024), Le droit des contrats à l’épreuve de l’économie de partage, Paris, Larcier, 804 p.
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Non-Invasive Neonatal Jaundice Detection via Two-Phase Self-Supervised Learning and Vision Transformer
Neonatal jaundice is a potentially serious and prevalent condition that can lead to neurological challenges in newborns if not detected or treated on time. Currently, most approaches employed to diagnose neonatal jaundice are invasive and are often characterized by constraints in accuracy and accessibility, especially in locations with limited resources. To proffer a solution to […]
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Leveraging digital twin and dynamic scheduling for enhanced human-robot collaboration
Industry 5.0 represents a paradigm shift toward human-centric, resilient, and sustainable production systems. At the core of this transformation lies digital twins, which enable predictive and prescriptive analytics in real time, improving decision-making capabilities such as visibility, transparency, and collaboration. By integrating advanced AI algorithms for data interpretation and facilitating seamless human-machine interactions, digital twins […]
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A Review on Financial Fraud Detection: Techniques, Challenges, Solutions, and Perspectives
Financial fraud is one of the most serious criminal activities, resulting in losses exceeding hundreds of billions of dollars each year. Most existing fraud detection frameworks still use static rule sets or traditional Machine Learning (ML) models, which fail with decentralized systems characterized by anonymity and dynamic behavior. Despite recent developments, the deployment of advanced […]
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A Review on Hierarchical Federated Learning: Architectures and Learning Algorithms
The rapid advancement of Hierarchical Federated Learning (HFL) has motivated researchers to explore novel algorithms and design strategies to address core challenges such as statistical heterogeneity, communication efficiency, and scalability. This study presents a comprehensive review of recent contributions over the past five years, focusing on HFL algorithms, including their architectural design and classification according […]
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Securing Digital Twin System Using Blockchain: Application on Smart Home
Digital twins (DTs) offer a virtual representation of physical entities, enabling advanced monitoring, control, and predictive analysis, particularly in Internet of Things (IoT) environments. However, the integration of DTs in smart homes raises significant security and privacy concerns due to the volume of sensitive data generated and exchanged. This paper proposes a secure architecture for […]
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A Comparative Analysis of Service Management Techniques in the Internet of Things
The Internet of Things (IoT) interconnects vast networks of heterogeneous devices across dynamic domains such as healthcare, industry, and smart cities, presenting critical challenges in real-time orchestration, resource efficiency, security, and scalability. To address these demands, diverse service management paradigms have emerged as essential frameworks. This review systematically analyzes existing IoT service management approaches, categorizing […]
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A Review of Digital Twins in Smart Environments
Transcending static digital representations, a Digital Twin (DT) functions as a dynamic, computational counterpart of a physical asset, capturing its real-time state and behavior through continuous data exchange. This mirroring capability positions DTs as a key enabler of intelligent operations in complex smart environments, from optimizing energy usage in buildings to managing urban infrastructure and […]