Jun Li

Efficient Bayesian model updating of large-scale bridges based on physics-informed neural networks surrogate model

Yong-shen Lei, Jun Li, Hong Hao

CoDe-SSM: Context-Detail Decoupled State Space Model for Efficient UHD Image Restoration

Jiaxu Su, Zhijian Wu, Jun Li, Bo Zhang, Yefeng Zheng

Ultra-high-definition (UHD) image restoration must balance the aggregation of spatially recurring degradation cues with the preservation of localized image structures. Compact aggregation can reduce redundant processing but may attenuate edges, textures, and other fine structures…Read more

Early prediction of intensive care unit-acquired weakness using quadriceps ultrasound and routine clinical variables: development and temporal validation of a prospective multicentre machine-learning model

Tongjuan Zou, 陈雪华, Jun Li, Xianying Lei, Hengyu Cai, Li Zhang, et al.

Intensive care unit-acquired weakness (ICUAW) is frequent in critically ill adults and is associated with adverse outcomes, but early recognition is difficult because standard diagnosis relies on volitional strength testing. In this prospective multicentre cohort study across 16…Read more

Methodology and Practice of Hong Kong 3D Digital Map Construction Based on Multi-Source Data Fusion

Li Chen, Jun Li, Yaping Wang, Jing Wang, Weichen Yao

Abstract. In response to Hong Kong's smart city development strategy, this paper takes the 3D digital map construction project in Kowloon as a practical case study and systematically presents a construction method for 3D digital mapping based on multi-source data fusion. Aiming a…Read more

Convergence-Latency-Aware Adaptive Modulation and Resource Allocation in RIS-Assisted Wireless Federated Learning

Liwei Wang, Wen Chen, Jun Li, Qingqing Wu, Ming Ding, Xusheng Zhu, et al.

Federated learning (FL) over wireless networks suffers from significant training latency and degraded convergence due to unreliable wireless transmission, especially under blocked propagation environments. Although reconfigurable intelligent surfaces (RISs) can improve communicat…Read more

Pipelined Gradient Coding

Xian Su, Jun Li

In large-scale machine learning, distributed training commonly involves multiple workers evaluating the gradients of the model on different dataset partitions. A common challenge is the presence of straggling workers, which may significantly slow down training. Traditional gradie…Read more

A Covert Precision Satellite Communication Framework Assisted by Cooperative IRSs

Haoyang Wu, Yunfan Bai, Mei Shen, Yuwen Qian, Guangji Chen, Long Shi, et al.

Satellite communication (SatCom), as an effective complement to terrestrial networks, has attracted considerable attention from both academia and industry owing to its wide coverage and high flexibility. However, the inherent openness of satellite links renders them highly vulner…Read more

SinD 2.0: A Multi-City UAV Dataset with Semantic Risk Annotations for SOTIF-Oriented Safety Validation at Signalized Intersections

Yunwei Li, Shengjie Fu, Chunrong Chen, Chengxiang Zhao, Yuchen Fan, Mingyu Zhu, et al.

Safety validation at signalized intersections remains a critical bottleneck for the deployment of autonomous driving systems (ADS), as these scenarios involve dense heterogeneous traffic, contested right of way, and long-tail safety-critical interactions, posing significant chall…Read more

CANN Bench: Benchmarking Agent Generated Kernels against Real NPU and Algorithmic Limits

Xue-Jian Gao, Deng Pan, Yueming Su, Jiasheng Li, Bin Du, Fengming Zhu, et al.

AI agents are now capable of writing, compiling, and iteratively optimizing low-level operator kernels on different hardware platforms. Existing benchmarks, however, focus almost exclusively on CUDA and Triton, leaving hardware ecosystems with less-exposed programming models with…Read more

ImputeECG: Deep Learning Reconstruction of Complete 12-Lead Electrocardiograms from Incomplete Recordings for Cardiac Assessment

Xiaocheng Fang, Haoyu Wang, Jieyi Cai, Qinghao Zhao, Jun Li, Shanwei Zhang, et al.

Complete digital 12-lead electrocardiograms (ECGs) are essential for AI-enabled cardiovascular assessment, yet many clinical ECG records, particularly those digitized from ECG images, remain incomplete because of short display formats, incomplete waveform digitization, lead loss,…Read more

Benchmarking Multi-Modal Graph-based Social Media Popularity Prediction

Utkarsh Sahu, Zhisheng Qi, Li Zhu, Yizhao Yang, Jun Li, Ryan Rossi, et al.

Social media popularity prediction aims to forecast the future reach or influence of online content from early-stage observations. Accurate prediction enables key downstream applications, such as advertising optimization and strategic content planning by users, creators, and plat…Read more

A Comparative Study of Machine Learning and Deep Learning Models for Real-Time UAV Positioning Error Estimation

Mei Yang, Hua Zhuo, Jun-Gang Ma, Guo-Hui Niu, Zulmira Mamtimin, Mei Tao, et al.

Accurate real-time positioning of Unmanned Aerial Vehicles (UAVs) is critical for navigation and mapping but remains challenging in complex environments due to signal blockages and multipath effects. This study presents a comparative framework for real-time error prediction of th…Read more

A Data-Driven Approach for Automatic Aircraft Engine Borescope Inspection Defect Detection Using Computer Vision and Deep Learning

Thibaud Schaller, Jun Li, Karl W. Jenkins

Regular aircraft engine inspections play a crucial role in aviation safety. However, traditional inspections are often performed manually, relying heavily on the judgment and experience of operators. This paper presents a data-driven deep learning framework capable of automatical…Read more

Advanced machine learning approaches for predicting energy and fossil fuel consumption for green growth

Song Li, Lei Luo, Jun Li