Particle Video for Crowd Flow Tracking - Entry-Exit Area and Dynamic Occlusion Detection. - Antoine Fagette; Patrick Jamet; Daniel Racoceanu; Jean-Yves Dufour (ICPRAM, 2014)

Statistically Representative Cloud of Particles for Crowd Flow Tracking. - Patrick Jamet; Stephen Chai Kheh Chew; Antoine Fagette; Jean-Yves Dufour; Daniel Racoceanu (ICPRAM (Selected Papers), 2014)

Unsupervised dense crowd detection by multiscale texture analysis. - Antoine Fagette; Nicolas Courty; Daniel Racoceanu; Jean-Yves Dufour (Pattern Recognit. Lett., 2014)

Using Social Sciences to Enhance the Realism of Simulation for Complex Urban Environments. - Stephen Chai Kheh Chew; Mohd. Faisal Bin Zainal Abiden; Hui Min Ng; Shawn Thian; Sidney Tio; Serge Landry; Antoine Fagette (CSDM Asia, 2016)

Simulating crowd motion using density estimation and optical flow. - Di Chen; Gary S. H. Tan; Antoine Fagette; Stephen Chai (WSC, 2017)

A Probabilistic Tensor Factorization Approach to Detect Anomalies in Spatiotemporal Traffic Activities. - Xudong Wang; Antoine Fagette; Pascal Sartelet; Lijun Sun 001 (ITSC, 2019)

Passive sensor planning for TDOA/FDOA geolocation under communication constraints. - Hugo Seuté; Laurent Ratton; Antoine Fagette (FUSION, 2020)

Increasing attacker engagement on SSH honeypots using semantic embeddings of cyber-attack patterns and deep reinforcement learning. - Junior Samuel López-Yépez; Antoine Fagette (SSCI, 2022)

Densifying SLAM for UAV Navigation by Fusion of Monocular Depth Prediction. - Yassine Habib; Panagiotis Papadakis; Cédric Le Barz; Antoine Fagette; Tiago Gonçalves; Cédric Buche (ICARA, 2023)

AI Agents Learning Human Decision Policies for Collaborative Situation Assessment in NORAD C2 Operations. - Tanya S. Paul; Daniel Lafond; Filipe Carvalhais Sanches; Jean-Sébastien Thivierge; Antoine Fagette (ICHMS, 2024)

Leveraging A* Pathfinding for Efficient Deep Reinforcement Learning in Obstacle-Dense Environments. - Junior Samuel López-Yépez; Antoine Fagette; Charles Dansereau; Filipe Carvalhais Sanches (ICMLA, 2024)

Real-time, dense UAV mapping by leveraging monocular depth prediction with monocular-inertial SLAM. - Yassine Habib; Panagiotis Papadakis; Cédric Le Barz; Antoine Fagette; Tiago Gonçalves; Cédric Buche (Adv. Robotics, 2024)

A Systematic Approach to Design Real-World Human-in-the-Loop Deep Reinforcement Learning: Salient Features, Challenges and Trade-offs. - Jalal Arabneydi; Md. Saiful Islam 007; Srijita Das 001; Sai Krishna Gottipati; William Duguay; Clodéric Mars; Matthew E. Taylor; Matthew Guzdial; Antoine Fagette; Younes Zerouali (CoRR, 2025)

Human-AI collaboration in real-world complex environment with reinforcement learning. - Md. Saiful Islam 007; Srijita Das 001; Sai Krishna Gottipati; William Duguay; Clodéric Mars; Jalal Arabneydi; Antoine Fagette; Matthew Guzdial; Matthew E. Taylor (Neural Comput. Appl., 2025)