Research on mechanical automatic food packaging defect detection model based on improved YOLOv5 algorithm.

ABSTRACT: With the rapid development of industrial automation, traditional manual detection methods are inefficient and error-prone, which cannot meet the needs of modern production for high efficiency and high precision. Therefore, it is particularly important to develop a mechanical automatic inspection system that can automatically identify food packaging defects. In this study, aiming at the limitations of existing technologies in identifying small targets and subtle defects, an enhanced YOLOv5-based model for detecting food packaging flaws is introduced. Firstly, we integrated a Convolutional Attention module (CBAM) to enhance the model's attention on crucial image features. This mechanism prioritizes significant features by weighting the feature map in channel and spatial dimensions, which imp

SUBMITTER: Liu G 

PROVIDER: S-EPMC12021230 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature