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Lightweight object detection model for food freezer warehouses
Jiayu Yang1, Zhihong Liang2, Mingming Qin1
1Institute of Big Data and Artificial Intelligence, Southwest Forestry University, Kunming, China.
Scientific Reports
|January 20, 2025
Summary
This study introduces the YOLOv8-RSS model for intelligent food freezer warehouse management. It enhances safety and efficiency by accurately detecting personnel and forklifts in challenging low-temperature environments.
Area of Science:
- Logistics and Supply Chain Management
- Artificial Intelligence in Warehousing
- Computer Vision for Industrial Safety
Background:
- Food freezer warehouses are critical but face challenges with high-density storage and extreme temperatures.
- Traditional management methods are insufficient for improving efficiency and mitigating safety risks in these environments.
- Intelligent and digital solutions are needed for enhanced warehouse operations.
Purpose of the Study:
- To propose a novel, lightweight, and high-precision object detection model (YOLOv8-RSS) for food freezer warehouse applications.
- To improve the efficiency and safety of operations within food freezer warehouses.
- To enable precise and rapid detection of personnel and forklifts in complex warehouse settings.
Main Methods:
- Development of the YOLOv8-RSS model, incorporating a novel C2f_RDB module for enhanced accuracy and reduced computational load.
- Application of the SimAM attention mechanism to the Backbone's final layer for focused image analysis without parameter increase.
- Implementation of Soft-Non-Maximum Suppression (Soft-NMS) to improve detection accuracy over traditional NMS.
Main Results:
- The YOLOv8-RSS model achieved a reduction of 0.05 M in parameter count and 0.8 G in FLOPs.
- Detection accuracy improved, with mAP@0.5 increasing by 1.4% and mAP@0.5:0.95 by 3.9%.
- The model demonstrated effective detection of personnel and forklifts in food freezer warehouse datasets.
Conclusions:
- The YOLOv8-RSS model offers a lightweight and high-precision solution for object detection in food freezer warehouses.
- It provides strong technical support for addressing complex detection demands and enhancing operational safety and efficiency.
- The model holds significant application value for modernizing food freezer warehouse management systems.
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