6 citations · 6 across the 2 of their papers we have counts for
7 papers
FLAME 3 Dataset: Unleashing the Power of Radiometric Thermal UAV Imagery for Wildfire Management
Bryce Hopkins, Leo ONeill, Michael Marinaccio +7
The increasing accessibility of radiometric thermal imaging sensors for unmanned aerial vehicles (UAVs) offers significant potential for advancing AI-driven aerial wildfire managem…
FlameVQA: A Physically-Grounded UAV Wildfire VQA Benchmark with Radiometric Thermal Supervision
Mobin Habibpour, John Spodnik, Niloufar Alipour Talemi +1
Wildfire monitoring from UAVs requires reliable reasoning over complex aerial scenes, where smoke, scale variation, and occlusions often limit RGB-only interpretation. We introduce…
FIRE-VLM: A Vision-Language-Driven Reinforcement Learning Framework for UAV Wildfire Tracking in a Physics-Grounded Fire Digital Twin
Chris Webb, Mobin Habibpour, Mayamin Hamid Raha +3
Wildfire monitoring demands autonomous systems capable of reasoning under extreme visual degradation, rapidly evolving physical dynamics, and scarce real-world training data. Exist…
Think, Remember, Navigate: Zero-Shot Object-Goal Navigation with VLM-Powered Reasoning
Mobin Habibpour, Fatemeh Afghah
While Vision-Language Models (VLMs) are set to transform robotic navigation, existing methods often underutilize their reasoning capabilities. To unlock the full potential of VLMs…
FIRETWIN: Digital Twin Advancing Multi-Modal Sensing, Interactive Analytics for Wildfire Response
Mayamin Hamid Raha, Ali Reza Tavakkoli, Chris Webb +4
Current wildfire management systems lack integrated virtual environments that combine historical data with immersive digital representations, hindering deep analysis and effective…
History-Augmented Vision-Language Models for Frontier-Based Zero-Shot Object Navigation
Mobin Habibpour, Fatemeh Afghah
Object Goal Navigation (ObjectNav) challenges robots to find objects in unseen environments, demanding sophisticated reasoning. While Vision-Language Models (VLMs) show potential,…