22 citations · 28 across the 13 of their papers we have counts for
13 papers
Fusing Urban Structure and Semantics: A Conditional Diffusion Model for Cross-City OD Matrix Generation
Bin Chen, Zhuoya Meng, Fang Yang +5
Accurate modeling of commuting flows is important for urban governance, traffic planning, and resource allocation. However, the combined influence of individual intentions, geograp…
A2DEPT: Large Language Model-Driven Automated Algorithm Design via Evolutionary Program Trees
Bin Chen, Shouliang Zhu, Beidan Liu +4
Designing heuristics for combinatorial optimization problems (COPs) is a fundamental yet challenging task that traditionally requires extensive domain expertise. Recently, Large La…
A Comprehensive Survey on Underwater Acoustic Target Positioning and Tracking: Progress, Challenges, and Perspectives
Zhong Yang, Zhengqiu Zhu, Yong Zhao +16
Underwater target tracking technology plays a pivotal role in marine resource exploration, environmental monitoring, and national defense security. Given that acoustic waves repres…
A Multi-Agent Reinforcement Learning Approach for Cooperative Air-Ground-Human Crowdsensing in Emergency Rescue
Wenhao Lu, Zhengqiu Zhu, Yong Zhao +5
Mobile crowdsensing is evolving beyond traditional human-centric models by integrating heterogeneous entities like unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGV…
DLW-CI: A Dynamic Likelihood-Weighted Cooperative Infotaxis Approach for Multi-Source Search in Urban Environments Using Consumer Drone Networks
Xiaoran Zhang, Yatai Ji, Yong Zhao +3
Consumer-grade drones equipped with low-cost sensors have emerged as a cornerstone of Autonomous Intelligent Systems (AISs) for environmental monitoring and hazardous substance det…
GeoNav: Empowering MLLMs with dual-scale geospatial reasoning for language-goal aerial navigation
Haotian Xu, Yue Hu, Chen Gao +4
Language-goal aerial navigation requires UAVs to localize targets in the complex outdoors, such as urban blocks based on textual instructions. The indoor methods are often hard to…