On the information selection for optimal data association. - Hind Laghmara; Christophe Cudel; Jean-Philippe Lauffenburger; Mohammed Boumediene (FUSION, 2017)

Evidential Object Association Using Heterogeneous Sensor Data. - Hind Laghmara; Christophe Cudel; Jean-Philippe Lauffenburger; Mohammed Boumediene (FUSION, 2018)

2.5D Evidential Grids for Dynamic Object Detection. - Hind Laghmara; Thomas Laurain; Christophe Cudel; Jean-Philippe Lauffenburger (FUSION, 2019)

Obstacle Avoidance, Path Planning and Control for Autonomous Vehicles. - Hind Laghmara; Mohamed Taha Boudali; Thomas Laurain; Jonathan Ledy; Rodolfo Orjuela; Jean-Philippe Lauffenburger; Michel Basset (IV, 2019)

Heterogeneous sensor data fusion for multiple object association using belief functions. - Hind Laghmara; Thomas Laurain; Christophe Cudel; Jean-Philippe Lauffenburger (Inf. Fusion, 2020)

A belief function-based forecasting link breakage indicator for VANETs. - Soumia Bourebia; Hind Laghmara; Benoît Hilt; Frédéric Drouhin; Sébastien Bindel; Jonathan Ledy; Jean-Philippe Lauffenburger; Pascal Lorenz (Wirel. Networks, 2020)

Neural Network Observer for Lateral Vehicle Model with Varying Sampled and Delayed Output. - Hasan Abdl Ghani; Hind Laghmara; Sofiane Ahmed Ali; Samia Ainouz 001 (CDC, 2023)

Sampled Data Radial Basis Function Neural Network Observer Design for Nonlinear Vehicle Dynamics. - Hasan Abdl Ghani; Hind Laghmara; Sofiane Ahmed Ali; Samia Ainouz 001; Redouane Khemmar (ACC, 2024)

A Conflict-Guided Evidential Multimodal Fusion for Semantic Segmentation. - Lucas Deregnaucourt; Hind Laghmara; Alexis Lechervy; Samia Ainouz 001 (WACV, 2025)

Overview on evidential fusion approaches in the context of collaborative perception for occupancy modeling. - Safa Ben Ayed; Jihed Dachraoui; Hind Laghmara; Rémi Boutteau (Appl. Intell., 2025)