Zobrazeno 1 - 10
of 104
pro vyhledávání: '"Ashqar, Huthaifa I"'
This study aims to comprehensively review and empirically evaluate the application of multimodal large language models (MLLMs) and Large Vision Models (VLMs) in object detection for transportation systems. In the first fold, we provide a background a
Externí odkaz:
http://arxiv.org/abs/2409.18286
Urban traffic management faces significant challenges due to the dynamic environments, and traditional algorithms fail to quickly adapt to this environment in real-time and predict possible conflicts. This study explores the ability of a Large Langua
Externí odkaz:
http://arxiv.org/abs/2408.00948
Autor:
Elhenawy, Mohammed, Abutahoun, Ahmad, Alhadidi, Taqwa I., Jaber, Ahmed, Ashqar, Huthaifa I., Jaradat, Shadi, Abdelhay, Ahmed, Glaser, Sebastien, Rakotonirainy, Andry
Multimodal Large Language Models (MLLMs) harness comprehensive knowledge spanning text, images, and audio to adeptly tackle complex problems, including zero-shot in-context learning scenarios. This study explores the ability of MLLMs in visually solv
Externí odkaz:
http://arxiv.org/abs/2407.00092
The integration of thermal imaging data with Multimodal Large Language Models (MLLMs) constitutes an exciting opportunity for improving the safety and functionality of autonomous driving systems and many Intelligent Transportation Systems (ITS) appli
Externí odkaz:
http://arxiv.org/abs/2406.13898
Traditional approaches to safety event analysis in autonomous systems have relied on complex machine learning models and extensive datasets for high accuracy and reliability. However, the advent of Multimodal Large Language Models (MLLMs) offers a no
Externí odkaz:
http://arxiv.org/abs/2406.13894
Object detection is a critical component of transportation systems, particularly for applications such as autonomous driving, traffic monitoring, and infrastructure maintenance. Traditional object detection methods often struggle with limited data an
Externí odkaz:
http://arxiv.org/abs/2406.10712
Recently, with the rapid development in the fields of technology and the increasing amount of text t available on the internet, it has become urgent to develop effective tools for processing and understanding texts in a way that summaries the content
Externí odkaz:
http://arxiv.org/abs/2406.07692
Autor:
Nafaa, Selvia, Essam, Hafsa, Ashour, Karim, Emad, Doaa, Mohamed, Rana, Elhenawy, Mohammed, Ashqar, Huthaifa I., Hassan, Abdallah A., Alhadidi, Taqwa I.
Monitoring asset conditions is a crucial factor in building efficient transportation asset management. Because of substantial advances in image processing, traditional manual classification has been largely replaced by semi-automatic/automatic techni
Externí odkaz:
http://arxiv.org/abs/2406.07674
This paper describes the creation, optimization, and assessment of a question-answering (QA) model for a personalized learning assistant that uses BERT transformers customized for the Arabic language. The model was particularly finetuned on science t
Externí odkaz:
http://arxiv.org/abs/2406.08519
Question generation for education assessments is a growing field within artificial intelligence applied to education. These question-generation tools have significant importance in the educational technology domain, such as intelligent tutoring syste
Externí odkaz:
http://arxiv.org/abs/2406.08520