YOLO-BGS Optimizes Textile Production Processes: Enhancing YOLOv8n with Bi-Directional Feature Pyramid Network and Global and Shuffle Attention Mechanisms for Efficient Fabric Defect Detection

Gege Lu, Tian Xiong and Gaihong Wu ()
Additional contact information
Gege Lu: College of Textile Engineering, Taiyuan University of Technology, Jinzhong 030600, China
Tian Xiong: College of Textile Engineering, Taiyuan University of Technology, Jinzhong 030600, China
Gaihong Wu: College of Textile Engineering, Taiyuan University of Technology, Jinzhong 030600, China

Sustainability, 2024, vol. 16, issue 18, 1-18

Abstract: Timely detection of fabric defects is crucial for improving fabric quality and reducing production losses for companies. Traditional methods for detecting fabric defects face several challenges, including low detection efficiency, poor accuracy, and limited types of detectable defects. To address these issues, this paper chose the YOLOv8n model for continuous iteration enhancement in order to improve its detection performance. First, multiscale feature fusion was realized by the Bi-directional Feature Pyramid Network (BiFPN). Second, the Shuffle Attention Mechanism (SA) is introduced to optimize feature classification. Finally, the Global Attention Mechanism (GAM) was used to improve global detection accuracy. Empirical findings demonstrated the improved model’s efficacy, attaining a test set mean average precision ( mAP ) value of 96.6%, which is an improvement of 3.6% compared to the original YOLOv8n. This validates that YOLO-BGS excels in detecting textile defects. It effectively locates these defects, minimizes resource waste, and fosters sustainable production practices.

Keywords: production losses; fabric defect; YOLOv8n; attention mechanism; feature extraction (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2071-1050/16/18/7922/pdf (application/pdf)
https://www.mdpi.com/2071-1050/16/18/7922/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:16:y:2024:i:18:p:7922-:d:1475564

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().