Carton Detection in Warehousing Logistics Based on Improved YOLOv8n

GAO Tong; SHEN Congcong; MING Yanjiao; JU Hongmei; WANG Meiling

doi:10.19554/j.cnki.1001-3563.2026.15.019

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Packaging Engineering ›› 2026, Vol. 47 ›› Issue (15) : 188-197. DOI: 10.19554/j.cnki.1001-3563.2026.15.019

Automatic and Intelligent Technology

Carton Detection in Warehousing Logistics Based on Improved YOLOv8n

GAO Tong, SHEN Congcong^*, MING Yanjiao, JU Hongmei, WANG Meiling

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Abstract

The work aims to propose an improved YOLOv8n object detection method named YOLOv8n-CBF to address the challenges of complex background interference, object occlusion, and missed detection of small objects in stacked carton detection within modern logistics warehousing scenarios. First, a Convolutional Block Attention Module (CBAM) was embedded before the SPPF module in the backbone network to suppress background noise. Second, a Bidirectional Feature Pyramid Network (BiFPN) was adopted to replace the PANet structure, achieving weighted bidirectional fusion of cross-scale features. Finally, a 160×160 high-resolution small-object detection layer (Four) was added, combined with Distribution Focal Loss and Complete-IoU Loss to improve localization accuracy. Ablation and comparative experiments were conducted on the publicly available LSCD and OSCD datasets. Ablation results demonstrated that the YOLOv8n-CBF algorithm achieved 84.6% mean average precision (mAP@0.5) on the LSCD dataset, representing an improvement of 3.3% over the YOLOv8n algorithm, and attained 96.8% mAP@0.5 on the OSCD dataset, surpassing YOLOv8n by 3.0%. Compared with mainstream YOLO series models, the proposed model achieves optimal detection accuracy with slightly increased computational complexity. The proposed strategies effectively enhance the model's feature extraction and multi-scale fusion capabilities, significantly improving detection accuracy and small-object perception in complex scenarios, thereby providing technical support for automated warehouse management.

Key words

stacked carton / YOLOv8n / attention mechanism / multi-scale feature enhancement / small object detection

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GAO Tong, SHEN Congcong, MING Yanjiao, JU Hongmei, WANG Meiling. Carton Detection in Warehousing Logistics Based on Improved YOLOv8n[J]. Packaging Engineering. 2026, 47(15): 188-197 https://doi.org/10.19554/j.cnki.1001-3563.2026.15.019

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