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Jun Ma

5 papers indexed

openalexBioengineering2026-07-23

AI-Driven Robotic PCI: A Perception-to-Action Framework for Coronary Guidewire Control

Zijing Liu, Huanming Xu, Zhendong Liu, Jun Ma, J I N Liu, Pengfei Bi, et al.

Robotic percutaneous coronary intervention (PCI) remains predominantly teleoperated, while the most demanding part of the procedure, guidewire navigation through a moving coronary tree under fluoroscopy, still depends on the continuous human interpretation of vessel anatomy, card…

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arxivcs.RO2026-06-29

Sphere-VIO: Fast and Robust Visual-Inertial Odometry via Unified Spherical Representation for Heterogeneous Multi-Camera Systems

Yueteng Yang, Yusen Xie, Hao Wei, Qianhao Wang, Boyu Zhou, Fei Gao, et al.

Multi-camera visual-inertial odometry (VIO) overcomes the inherent limitations of pure visual systems by expanding the field of view. However, existing algorithms are typically tailored for fixed camera setups and lack unified compatibility with heterogeneous multi-camera systems…

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crossrefSmart Cities2025-03-18Cited by 15

Environmental Justice in the 15-Minute City: Assessing Air Pollution Exposure Inequalities Through Machine Learning and Spatial Network Analysis

Feifeng Jiang, Jun Ma

The intersection of environmental justice and urban accessibility presents a critical challenge in sustainable city planning. While the “15-minute city” concept has emerged as a prominent framework for promoting walkable neighborhoods, its implications for environmental exposure…

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crossrefApplied Sciences2025-03-12

Development and Comparison of Machine Learning and Deep Learning Models for Speech Audiometry Prediction

Jae sung Shin, Jun Ma, Mao Makara, Nak-Jun Sung, Seong Jun Choi, Sung yeup Kim, et al.

Hearing loss significantly impacts daily communication, making accurate speech audiometry (SA) assessment essential for diagnosis and treatment. However, SA testing is time-consuming and resource-intensive, limiting its accessibility in clinical practice. This study aimed to deve…

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crossrefElectronics2024-11-19Cited by 2

Robust Twin Extreme Learning Machine Based on Soft Truncated Capped L1-Norm Loss Function

Zhendong Xu, Bo Wei, Guolin Yu, Jun Ma

Currently, most researchers propose robust algorithms from different perspectives for overcoming the impact of outliers on a model, such as introducing loss functions. However, some loss functions often fail to achieve satisfactory results when the outliers are large. Therefore,…

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