Hui Chen
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Hui Chen has a total of 3 co-authors. Here are the top co-authors by number of shared publications:
- Weifeng Hu
School of Digital Technology & Innovation Design, Jiangnan University, Wuxi 214122, China
2 shared publications - Yue Hu
School of Design, Jiangnan University, Wuxi 214122, China
2 shared publications - Qiang Wang
School of Design, Jiangnan University, Wuxi 214000, China
1 shared publication
Latest Publications
- Open Access
- 9 November 2026
- Published by MDPI AG in Applied Sciences
- Vol. 16 (21) , 11091
An Improved YOLO11n Model for Multiclass Object Detection of Chariot-and-Horse Elements in Images of Han Pictorial Stones
Han pictorial stones constitute an important component of China’s ancient cultural heritage, and their depictions of chariots, horses, and human figures provide valuable visual evidence for investigating travel activities in the Han dynasty. The identification and localization of chariot-and-horse elements provide a foundation for the retrieval and statistical analysis of relevant materials. However, current documentation practices rely largely on manual identification and transcription, limiting the efficiency of large-scale processing. In Han pictorial stone images, weak contours, textural interference, dense occlusion, and scale variation pose substantial challenges for reliable object detection. Accordingly, 539 images were collected and annotated with 3736 instances. Building on this dataset, an improved YOLO11n model was proposed, incorporating the RubbingDown multi-branch downsampling structure, C3k2GRM module, and task-adapted ASF multi-scale fusion pathway for information preservation, contextual representation, and cross-scale feature fusion. The proposed model achieved mAP@0.5, mAP@0.5:0.95, and recall of 88.0%, 54.5%, and 86.5%, respectively, representing improvements of 5.5, 2.8, and 9.9 percentage points, respectively, over the YOLO11n baseline. The model maintained 2.58 M parameters, while GFLOPs increased from 6.3 to 7.3. The detection outputs could support future workflows for documenting, retrieving, quantitatively analyzing, and manually verifying chariot-and-horse elements in Han pictorial stone images.
- 9 November 2026
- Published by MDPI AG in Applied Sciences
- Vol. 16 (21) , 11091
Open AccessAn Improved YOLO11n Model for Multiclass Object Detection of Chariot-and-Horse Elements in Images of Han Pictorial Stones
Han pictorial stones constitute an important component of China’s ancient cultural heritage, and their depictions of chariots, horses, and human figures provide valuable visual evidence for investigating travel activities in the Han dynasty. The identification and localization of chariot-and-horse elements provide a foundation for the retrieval and statistical analysis of relevant materials. However, current documentation practices rely largely on manual identification and transcription, limiting the efficiency of large-scale processing. In Han pictorial stone images, weak contours, textural interference, dense occlusion, and scale variation pose substantial challenges for reliable object detection. Accordingly, 539 images were collected and annotated with 3736 instances. Building on this dataset, an improved YOLO11n model was proposed, incorporating the RubbingDown multi-branch downsampling structure, C3k2GRM module, and task-adapted ASF multi-scale fusion pathway for information preservation, contextual representation, and cross-scale feature fusion. The proposed model achieved mAP@0.5, mAP@0.5:0.95, and recall of 88.0%, 54.5%, and 86.5%, respectively, representing improvements of 5.5, 2.8, and 9.9 percentage points, respectively, over the YOLO11n baseline. The model maintained 2.58 M parameters, while GFLOPs increased from 6.3 to 7.3. The detection outputs could support future workflows for documenting, retrieving, quantitatively analyzing, and manually verifying chariot-and-horse elements in Han pictorial stone images.
- Open Access
- 5 August 2026
- Published by MDPI AG in Sustainability
- Vol. 18 (15) , 7922
Designing Authentic Virtual Heritage Experiences for Sustainable Cultural Heritage Communication: A Mixed-Methods Study
Perceived authenticity may strengthen the credibility of virtual cultural heritage communication and foster sustained cultural engagement, yet authenticity theory remains insufficiently translated into actionable design guidance. This study employed an exploratory sequential mixed-methods design comprising ten qualitative interviews, exploratory and confirmatory factor analyses with two independent samples (n = 200 each), framework construction, and a between-group prototype evaluation (n = 61). The analyses indicated a context-specific two-factor structure: constructive authenticity, integrating evidence-based judgment, contextual interpretation, and narrative plausibility; and existential authenticity, encompassing participation, emotional engagement, personal meaning, and cultural connection. Objective authenticity converged with constructive authenticity rather than emerging independently, suggesting that users interpreted historical evidence through digitally mediated representations. These findings were translated into six coordinated design dimensions: historical environment design, historical information transparency, narrative plausibility, stylistic atmosphere, experiential immersion, and interactive engagement. In a single-theme comparison, the framework-guided prototype was associated with higher loyalty, satisfaction, cultural identity, and behavioral intention than the conventionally designed prototype (Hedges’ g = 1.265–1.636). Overall, the study offers a context-specific theoretical account and an actionable, evidence-informed framework that may support continued engagement and cultural transmission; long-term sustainability outcomes and cross-context transferability require further investigation.
- 5 August 2026
- Published by MDPI AG in Sustainability
- Vol. 18 (15) , 7922
Open AccessDesigning Authentic Virtual Heritage Experiences for Sustainable Cultural Heritage Communication: A Mixed-Methods Study
Perceived authenticity may strengthen the credibility of virtual cultural heritage communication and foster sustained cultural engagement, yet authenticity theory remains insufficiently translated into actionable design guidance. This study employed an exploratory sequential mixed-methods design comprising ten qualitative interviews, exploratory and confirmatory factor analyses with two independent samples (n = 200 each), framework construction, and a between-group prototype evaluation (n = 61). The analyses indicated a context-specific two-factor structure: constructive authenticity, integrating evidence-based judgment, contextual interpretation, and narrative plausibility; and existential authenticity, encompassing participation, emotional engagement, personal meaning, and cultural connection. Objective authenticity converged with constructive authenticity rather than emerging independently, suggesting that users interpreted historical evidence through digitally mediated representations. These findings were translated into six coordinated design dimensions: historical environment design, historical information transparency, narrative plausibility, stylistic atmosphere, experiential immersion, and interactive engagement. In a single-theme comparison, the framework-guided prototype was associated with higher loyalty, satisfaction, cultural identity, and behavioral intention than the conventionally designed prototype (Hedges’ g = 1.265–1.636). Overall, the study offers a context-specific theoretical account and an actionable, evidence-informed framework that may support continued engagement and cultural transmission; long-term sustainability outcomes and cross-context transferability require further investigation.