A new Evaluation Approach for Deep Learning-based Monocular Depth Estimation Methods. - Antoine Mauri; Redouane Khemmar; Rémi Boutteau; Benoit Decoux; Jean-Yves Ertaud; Madjid Haddad (ITSC, 2020)

Deep Learning for Real-Time 3D Multi-Object Detection, Localisation, and Tracking: Application to Smart Mobility. - Antoine Mauri; Redouane Khemmar; Benoit Decoux; Nicolas Ragot; Romain Rossi; Rim Trabelsi; Rémi Boutteau; Jean-Yves Ertaud; Xavier Savatier (Sensors, 2020)

Real-Time 3D Multi-Object Detection and Localization Based on Deep Learning for Road and Railway Smart Mobility. - Antoine Mauri; Redouane Khemmar; Benoit Decoux; Madjid Haddad; Rémi Boutteau (J. Imaging, 2021)

A Dataset for Temporal Semantic Segmentation Dedicated to Smart Mobility of Wheelchairs on Sidewalks. - Benoit Decoux; Redouane Khemmar; Nicolas Ragot; Arthur Venon; Marcos Grassi-Pampuch; Antoine Mauri; Louis Lecrosnier; Vishnu Pradeep (J. Imaging, 2022)

Lightweight convolutional neural network for real-time 3D object detection in road and railway environments. - Antoine Mauri; Redouane Khemmar; Benoit Decoux; Madjid Haddad; Rémi Boutteau (J. Real Time Image Process., 2022)

Road and Railway Smart Mobility: A High-definition Ground Truth Hybrid Dataset. - Redouane Khemmar; Antoine Mauri; Camille Dulompont; Jayadeep Gajula; Vincent Vauchey; Madjid Haddad; Rémi Boutteau (Sensors, 2022)

Prédiction et évitement d'obstacles basés deep learning : Application à la mobilité ferroviaire et routière. (Obstacle prediction and avoidance based on deep learning : Application to rail and road mobility). - Antoine Mauri (2022)

Improving the Efficiency of 3D Monocular Object Detection and Tracking for Road and Railway Smart Mobility. - Alexandre Evain; Antoine Mauri; François Garnier; Messmer Kounouho; Redouane Khemmar; Madjid Haddad; Rémi Boutteau; Sébastien Breteche; Sofiane Ahmedali (Sensors, 2023)