Research on intelligent safety management of e-commerce logistics storage through a deep learning model

This paper used You Only Look Once version 5 (YOLOv5) and the skeleton extraction algorithm to identify abnormal actions of logistics warehouse personnel. First, the skeleton of personnel actions in consecutive frames of images was obtained using the above two algorithms. Then, a back-propagation neural network (BPNN) was used as the classifier to identify the type of actions. Finally, simulation experiments were conducted. The proposed algorithm achieved strong personnel recognition and localization, skeleton extraction, and action type recognition, while maintaining stable performance when processing multi-person images.

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Publication Details

Journal
Discover Artificial Intelligence
Published
2026-10-05
DOI
https://doi.org/10.1007/s44163-026-02236-6
Primary Topic
Human Pose and Action Recognition
Type
article
Field-Weighted Citation Impact
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article

Research on intelligent safety management of e-commerce logistics storage through a deep learning model

Yufeng Zou, Yanxia Ma
Discover Artificial Intelligence
Human Pose and Action Recognition
article

Research on intelligent safety management of e-commerce logistics storage through a deep learning model

Yufeng Zou, Yanxia Ma
article en

Abstract

This paper used You Only Look Once version 5 (YOLOv5) and the skeleton extraction algorithm to identify abnormal actions of logistics warehouse personnel. First, the skeleton of personnel actions in consecutive frames of images was obtained using the above two algorithms. Then, a back-propagation neural network (BPNN) was used as the classifier to identify the type of actions. Finally, simulation experiments were conducted. The proposed algorithm achieved strong personnel recognition and localization, skeleton extraction, and action type recognition, while maintaining stable performance when processing multi-person images.

Discover Artificial IntelligenceVol. 6(1)
Shanghai Polytechnic University (CN)
Openalex Percentile: Top 14%
Human Pose and Action Recognition
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