6 papers
Enhancing Pavement Crack Classification with Bidirectional Cascaded Neural Networks
Taqwa I. Alhadidi, Asmaa Alazmi, Shadi Jaradat +3
Pavement distress, such as cracks and potholes, is a significant issue affecting road safety and maintenance. In this study, we present the implementation and evaluation of Bidirec…
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…
Visual Reasoning and Multi-Agent Approach in Multimodal Large Language Models (MLLMs): Solving TSP and mTSP Combinatorial Challenges
Mohammed Elhenawy, Ahmad Abutahoun, Taqwa I. Alhadidi +6
Multimodal Large Language Models (MLLMs) harness comprehensive knowledge spanning text, images, and audio to adeptly tackle complex problems, including zero-shot in-context learnin…
Object Detection using Oriented Window Learning Vi-sion Transformer: Roadway Assets Recognition
Taqwa Alhadidi, Ahmed Jaber, Shadi Jaradat +2
Object detection is a critical component of transportation systems, particularly for applications such as autonomous driving, traffic monitoring, and infrastructure maintenance. Tr…
Exploring Traffic Crash Narratives in Jordan Using Text Mining Analytics
Shadi Jaradat, Taqwa I. Alhadidi, Huthaifa I. Ashqar +2
This study explores traffic crash narratives in an attempt to inform and enhance effective traffic safety policies using text-mining analytics. Text mining techniques are employed…
Eyeballing Combinatorial Problems: A Case Study of Using Multimodal Large Language Models to Solve Traveling Salesman Problems
Mohammed Elhenawy, Ahmed Abdelhay, Taqwa I. Alhadidi +5
Multimodal Large Language Models (MLLMs) have demonstrated proficiency in processing di-verse modalities, including text, images, and audio. These models leverage extensive pre-exi…