29 citations · 32 across the 7 of their papers we have counts for
7 papers
A Dynamic Fusion Large Language Model for Traffic Flow Prediction
Xue Qiu, Jianli Xiao
Traffic flow prediction is a core supporting technology for intelligent transportation systems. It uses historical data to infer future traffic dynamics in specific areas, thereby…
FPMT: Enhanced Semi-Supervised Model for Traffic Incident Detection
Xinying Lu, Jianli Xiao
For traffic incident detection, the acquisition of data and labels is notably resource-intensive, rendering semi-supervised traffic incident detection both a formidable and consequ…
ST-RetNet: A Long-term Spatial-Temporal Traffic Flow Prediction Method
Baichao Long, Wang Zhu, Jianli Xiao
Traffic flow forecasting is considered a critical task in the field of intelligent transportation systems. In this paper, to address the issue of low accuracy in long-term forecast…
A Multi-Channel Spatial-Temporal Transformer Model for Traffic Flow Forecasting
Jianli Xiao, Baichao Long
Traffic flow forecasting is a crucial task in transportation management and planning. The main challenges for traffic flow forecasting are that (1) as the length of prediction time…
A Hybrid Model for Traffic Incident Detection based on Generative Adversarial Networks and Transformer Model
Xinying Lu, Doudou Zhang, Jianli Xiao
In addition to enhancing traffic safety and facilitating prompt emergency response, traffic incident detection plays an indispensable role in intelligent transportation systems by…
Hybrid Transformer and Spatial-Temporal Self-Supervised Learning for Long-term Traffic Prediction
Wang Zhu, Doudou Zhang, Baichao Long +1
Long-term traffic prediction has always been a challenging task due to its dynamic temporal dependencies and complex spatial dependencies. In this paper, we propose a model that co…
A New Method for Vehicle Logo Recognition Based on Swin Transformer
Yang Li, Doudou Zhang, Jianli Xiao
Intelligent Transportation Systems (ITS) utilize sensors, cameras, and big data analysis to monitor real-time traffic conditions, aiming to improve traffic efficiency and safety. A…