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phD
3D ultrasound imaging using orthogonal row and column addressing of the matrix array for ultrasonic NDT
This thesis is part of the activities of the Digital Instrumentation Department (DIN) in Non-Destructive Testing (NDT), and aims to design a new, fast and advanced 3D ultrasound imaging method using matrix arrays. The aim will be to produce three-dimensional ultrasound images of the internal volume of a structure that may contain defects (e.g. cracks),...
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phD
In-Sensor Computing for MEMS Sensors: Toward an Electromechanical Neural Network
The rise of machine learning models for processing sensor data has led to the development of Edge-AI, which aims to perform these data processing tasks locally, directly at the sensor level. This approach reduces the amount of data transmitted and eases the load on centralized computing centers, providing a solution to decrease the overall energy...
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phD
Digital reconstruction of an industrial tank for the improvement of real-time monitoring instrumentation
In the context of industrial digitalization and real-time monitoring, accessing 3D fields (velocity, viscosity, turbulence, concentration, etc.) in real time can be crucial, as local sensor networks are sometimes insufficient to provide a comprehensive view of the systemapos;s dynamics. This PhD project aims to investigate a methodology for the real-time reconstruction of fields within an...
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phD
Power and data transmission via an acoustic link for closed metallic environments
This thesis focuses on the transmission of power and data through metal walls using acoustic waves. Ultimately, this technology will be used to power, read and control systems located in areas enclosed in metal, such as pressure vessels, ship hulls and submarines. Because electromagnetic waves are absorbed by metal, acoustic waves are needed to communicate...
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phD
Efficient Multimodal Vision Transformers for Embedded System
The proposed thesis focuses on the optimization of multimodal vision transformers (ViT) for panoptic object segmentation, exploring two main directions. The first is to develop a versatile fusion pipeline to integrate multimodal data (RGB, IR, depth, events, point clouds) by leveraging inter-modal alignment relationships. The second is to investigate an approach combining pruning and mixed-precision...
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phD
Exploration of unsupervised approaches for modeling the environment from RADAR data
Radar technologies have gained significant interest in recent years, particularly with the emergence of MIMO radars and quot;Imaging Radars 4Dquot;. This new generation of radar offers both opportunities and challenges for the development of perception algorithms. Traditional algorithms such as FFT, CFAR, and DOA are effective for detecting moving targets, but the generated point clouds...
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