Lucile Rossi
Papers
1
Total Citations
21
H-Index
1
About
Lucile Rossi is a leading researcher in computer vision and human-robot interaction, with a specialized focus on wildland firefighting assistance. Her work bridges artificial intelligence and emergency response, particularly through the development of visual-attention-based systems that mimic human perception to aid firefighters in hazardous environments. Her most-cited paper, "A human-like visual-attention-based artificial vision system for wildland firefighting assistance" (2017, 21 citations), introduces a novel framework that enables autonomous systems to prioritize critical visual cues—such as fire fronts, smoke plumes, and escape routes—mirroring the cognitive strategies of experienced firefighters. This contribution has significant implications for enhancing situational awareness and decision-making under extreme conditions, reducing cognitive load on personnel. Rossi’s research integrates deep learning, gaze tracking, and scene understanding, positioning her at the forefront of applied AI for disaster management. Her work has been recognized for its practical impact, with applications in drone-based surveillance and wearable assistive technologies. By translating human attentional mechanisms into machine vision, Rossi is shaping the future of intelligent systems that can operate effectively in dynamic, life-threatening scenarios.
Research Focus
Key Achievements
Top Papers
- 1