Marielle Malfante
Commissariat à l'Énergie Atomique et aux Énergies Alternatives
Papers
1
Total Citations
6
H-Index
1
About
Marielle Malfante is a researcher whose work sits at the intersection of autonomous systems, sensor fusion, and real-time perception for robotics. Her primary research areas include occupancy grid mapping, vehicle detection, and the practical deployment of perception algorithms in dynamic environments. Malfante’s most cited work, “Vehicle Detection on Occupancy Grid Maps: Comparison of Five Detectors Regarding Real-Time Performance” (2023), provides a rigorous benchmark for evaluating detection algorithms on occupancy grid maps—a critical environment model that fuses data from multiple range sensors in real-time. By systematically comparing five different detectors, she offers actionable insights for autonomous vehicle systems, where accurate and fast detection is paramount. This contribution is especially valuable for researchers and engineers seeking to balance computational efficiency with detection reliability. While her citation count is still growing, Malfante’s work is notable for its practical focus on real-world performance constraints, making her a promising voice in the field of autonomous navigation and sensor-based perception.
Research Focus
Key Achievements
Top Papers
- 1