Younes Zegaoui

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Image analysis for Maintenance intervention request classification

Research /

Technologies and systems for automation of maintenance tasks and equipment management are used in several cases of different business fields like security or food-processing industry for instance. The technologies used have reached a maturation stage allowing their use in real case, according to practical application specificity. However, it remains uncertainties about developing an approach allowing […]

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Younes Zegaoui Ph.D. thesis defense : “Urban objects detection with 3D multi-sensor data registered continuously at the ground level”

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Tuesday 12th of October, Younes Zegaoui, Ph.D. Candidate in Montpellier University will defend his thesis named “Urban objects detection with 3D multi-sensor data registered continuously at the ground level”. His thesis defense will take place at LIRMM laboratory in Montpellier, France. The jury will be composed of François Goulette, Professor, Ecole MINES ParisTech, Sébastien Lefèvre, Professor, Bretagne Sud University, Géraldine Morin, Professor, Toulouse University, Christophe Fiorio, Professor, Montpellier University, Marc Chaumont, MCF HDR, Nîmes University, and

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Hey Artificial Intelligence! If you want to Scan Me, please do it in 3D!

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What if we could automatically count and detect objects and various pieces of equipment in a building? This would have a tremendous impact on inventory activities, daily inspections, making these tasks easier and faster. This is what we are trying to achieve here. The main idea consists in relying on depth cameras (such ad LiDAR,

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3D deep learning on terrestrial LiDAR scanned urban environments for objects monitoring

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Large urban agglomerations nowadays are facing some major issues such as economic restrictions, environmental challenges, global and systemic approaches in city management [8]. One of them is to precisely monitor urban objects which can be natural (trees), artificial (traffic lights or poles), static or moving (cars). This is essential to analyze their mutual interaction (for

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