activity
20222026
most citedChatGPT for Shaping the Future of Dentistry: The Potential of Multi-Modal Large Language Model

327 citations · 754 across the 17 of their papers we have counts for

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Showing 2023Show all

10 papers · 1 filter

cs.RO2023★ 1 cited

RF-Enhanced Road Infrastructure for Intelligent Transportation

Dajiang Suo, Heyi Li, Rahul Bhattacharyya +7

The EPC GEN 2 communication protocol for Ultra-high frequency Radio Frequency Identification (RFID) has offered a promising avenue for advancing the intelligence of transportation…

cs.AI2023

TrTr: A Versatile Pre-Trained Large Traffic Model based on Transformer for Capturing Trajectory Diversity in Vehicle Population

Ruyi Feng, Zhibin Li, Bowen Liu +1

Understanding trajectory diversity is a fundamental aspect of addressing practical traffic tasks. However, capturing the diversity of trajectories presents challenges, particularly…

cs.CL2023★ 10 cited

TrafficSafetyGPT: Tuning a Pre-trained Large Language Model to a Domain-Specific Expert in Transportation Safety

Ou Zheng, Mohamed Abdel-Aty, Dongdong Wang +2

Large Language Models (LLMs) have shown remarkable effectiveness in various general-domain natural language processing (NLP) tasks. However, their performance in transportation saf…

cs.LG2023★ 2 cited

Lane Change Intention Recognition and Vehicle Status Prediction for Autonomous Vehicles

Renteng Yuan, Mohamed Abdel-Aty, Xin Gu +2

Accurately detecting and predicting lane change (LC)processes of human-driven vehicles can help autonomous vehicles better understand their surrounding environment, recognize poten…

cs.CL2023★ 327 cited

ChatGPT for Shaping the Future of Dentistry: The Potential of Multi-Modal Large Language Model

Hanyao Huang, Ou Zheng, Dongdong Wang +8

The ChatGPT, a lite and conversational variant of Generative Pretrained Transformer 4 (GPT-4) developed by OpenAI, is one of the milestone Large Language Models (LLMs) with billion…

cs.RO2023★ 14 cited

AVOID: Autonomous Vehicle Operation Incident Dataset Across the Globe

Ou Zheng, Mohamed Abdel-Aty, Zijin Wang +3

Crash data of autonomous vehicles (AV) or vehicles equipped with advanced driver assistance systems (ADAS) are the key information to understand the crash nature and to enhance the…

stat.AP2023★ 3 cited

Exploratory analysis of injury severity under different levels of driving automation (SAE Level 2-5) using multi-source data

Shengxuan Ding, Mohamed Abdel-Aty, Natalia Barbour +3

Vehicles equipped with automated driving capabilities have shown potential to improve safety and operations. Advanced driver assistance systems (ADAS) and automated driving systems…

physics.soc-ph2023★ 3 cited

Traffic flow clustering framework using drone video trajectories to identify surrogate safety measures

Shengxuan Ding, Mohamed Abdel-Aty, Ou Zheng +2

The utilization of traffic conflict indicators is crucial for assessing traffic safety, especially when the crash data is unavailable. To identify traffic conflicts based on traffi…

cs.CV2023★ 81 cited

Advances and Applications of Computer Vision Techniques in Vehicle Trajectory Generation and Surrogate Traffic Safety Indicators

Mohamed Abdel-Aty, Zijin Wang, Ou Zheng +1

The application of Computer Vision (CV) techniques massively stimulates microscopic traffic safety analysis from the perspective of traffic conflicts and near misses, which is usua…

cs.CL2023★ 24 cited

ChatGPT is on the Horizon: Could a Large Language Model be Suitable for Intelligent Traffic Safety Research and Applications?

Ou Zheng, Mohamed Abdel-Aty, Dongdong Wang +2

ChatGPT embarks on a new era of artificial intelligence and will revolutionize the way we approach intelligent traffic safety systems. This paper begins with a brief introduction a…