1 citations · 2 across the 3 of their papers we have counts for
4 papers
Zero-Shot Scene Understanding with Multimodal Large Language Models for Automated Vehicles
Mohammed Elhenawy, Shadi Jaradat, Taqwa I. Alhadidi +4
Scene understanding is critical for various downstream tasks in autonomous driving, including facilitating driver-agent communication and enhancing human-centered explainability of…
Multimodal Large Language Models for Enhanced Traffic Safety: A Comprehensive Review and Future Trends
Mohammad Abu Tami, Mohammed Elhenawy, Huthaifa I. Ashqar
Traffic safety remains a critical global challenge, with traditional Advanced Driver-Assistance Systems (ADAS) often struggling in dynamic real-world scenarios due to fragmented se…
HazardNet: A Small-Scale Vision Language Model for Real-Time Traffic Safety Detection at Edge Devices
Mohammad Abu Tami, Mohammed Elhenawy, Huthaifa I. Ashqar
Traffic safety remains a vital concern in contemporary urban settings, intensified by the increase of vehicles and the complicated nature of road networks. Traditional safety-criti…
Vision-Language Models for Autonomous Driving: CLIP-Based Dynamic Scene Understanding
Mohammed Elhenawy, Huthaifa I. Ashqar, Andry Rakotonirainy +3
Scene understanding is essential for enhancing driver safety, generating human-centric explanations for Automated Vehicle (AV) decisions, and leveraging Artificial Intelligence (AI…