Article: Enhanced multimodal recognition and genealogy research of Maonan ethnic Nuo masks based on YOLOv10 and CLIP fusion approach Journal: International Journal of Information and Communication Technology (IJICT) 2026 Vol.27 No.92 pp.1 - 24 Abstract: This study addresses the recognition challenges of Maonan ethnic Nuo masks under complex backgrounds, varying lighting conditions, and multi-scale environments by proposing a 'detection-identification-analysis' multimodal framework. The front-end employs an improved YOLOv10 model (integrating EMA and GELU), while the back-end leverages CLIP and text description augmentation. A MNMD dataset comprising 2,850 images across 28 fine-grained categories was constructed. The enhanced model achieved an accuracy of 84.10% on the test set, with parameters reduced by 40.43% compared to YOLOv8, providing an effective solution for the digital preservation of cultural heritage. Inderscience Publishers - linking academia, business and industry through research

Title: Enhanced multimodal recognition and genealogy research of Maonan ethnic Nuo masks based on YOLOv10 and CLIP fusion approach

Authors: Ling Zhao

Addresses: College of the Arts, Guangxi Minzu University, Nanning, 530000, China

Abstract: This study addresses the recognition challenges of Maonan ethnic Nuo masks under complex backgrounds, varying lighting conditions, and multi-scale environments by proposing a 'detection-identification-analysis' multimodal framework. The front-end employs an improved YOLOv10 model (integrating EMA and GELU), while the back-end leverages CLIP and text description augmentation. A MNMD dataset comprising 2,850 images across 28 fine-grained categories was constructed. The enhanced model achieved an accuracy of 84.10% on the test set, with parameters reduced by 40.43% compared to YOLOv8, providing an effective solution for the digital preservation of cultural heritage.

Keywords: Maonan ethnic Nuo masks; multimodal recognition; YOLOv10; CLIP; lineage analysis.

DOI: 10.1504/IJICT.2026.155944

International Journal of Information and Communication Technology, 2026 Vol.27 No.92, pp.1 - 24

Received: 05 Apr 2026
Accepted: 29 Apr 2026
Published online: 26 Aug 2026 *

Title: Enhanced multimodal recognition and genealogy research of Maonan ethnic Nuo masks based on YOLOv10 and CLIP fusion approach

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