Yujing Chen

ORCID: 0009-0008-9905-4004
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About
Contact & Profiles
Research Areas
  • Gait Recognition and Analysis
  • Diverse Musicological Studies
  • Video Surveillance and Tracking Methods
  • Hand Gesture Recognition Systems
  • Human Pose and Action Recognition
  • Inflammatory Biomarkers in Disease Prognosis
  • Architecture and Cultural Influences
  • Drug Transport and Resistance Mechanisms
  • Folklore, Mythology, and Literature Studies
  • Digital Image Processing Techniques
  • Image and Object Detection Techniques
  • Cancer, Lipids, and Metabolism
  • E-commerce and Technology Innovations
  • Energy, Environment, Economic Growth
  • Medical Image Segmentation Techniques

Jilin Medical University
2024

Jilin University
2024

Southeast University
2023

Zhejiang Chinese Medical University
2023

Guangdong University of Finance
2018

Zibo Vocational Institute
2011

China Three Gorges University
2007-2010

10.1007/s11356-023-30076-9 article EN Environmental Science and Pollution Research 2023-10-03

<title>Abstract</title> Gait recognition, an emerging field at the intersection of computer vision and biometrics, has garnered significant attention for its potential applications in surveillance, security, healthcare. In this paper, we present a novel method that combines appearance-based gait recognition with human height data. The proposed approach aims to enhance accuracy robustness systems by incorporating complementary features derived from both patterns height. We believe information...

10.21203/rs.3.rs-4478986/v1 preprint EN cc-by Research Square (Research Square) 2024-06-11

<title>Abstract</title> Gait recognition, an emerging field at the intersection of computer vision and biometrics, has garnered significant attention for its potential applications in surveillance, security, healthcare. In this paper, we present a novel method that combines appearance-based gait recognition with human height data. The proposed approach aims to enhance accuracy robustness systems by incorporating complementary features derived from both patterns height. We believe information...

10.21203/rs.3.rs-4546317/v1 preprint EN cc-by Research Square (Research Square) 2024-06-21
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