Deformation And Penetration Hybrid Detection-Net For Parcels Inspection In Industrial Supply Chain
Zhi Chen, Cuifeng Du, Xiujie Huang, Zelong Lin, Yuyu Zhou, Quanlong Guan, Zhefu Li, Shuanghuan Lv
Abstract
The express delivery industry has become integral to modern social life, but supply chain parcels, especially those made of corrugated cardboard, are at risk of damage during transportation. Although corrugated cardboard boxes offer some impact resistance, they can still experience deformation and penetration damage. To address this issue, we propose a hybrid model called Parcels-DNet. Parcels-DNet adopts a lightweight feature extraction backbone network, enabling deployment in resource-constrained scenarios like mobile or embedded devices. Additionally, our experimental results demonstrate that Parcels-DNet effectively captures the features of parcel deformation and penetration damage. This improves the safety and efficiency of express supply chain parcel transportation, offering greater convenience and economic benefits for the logistics industry.
BibTeX
@inproceedings{icassp2024_deformationandpe,
title = {Deformation And Penetration Hybrid Detection-Net For Parcels Inspection In Industrial Supply Chain},
author = {Zhi Chen and Cuifeng Du and Xiujie Huang and Zelong Lin and Yuyu Zhou and Quanlong Guan and Zhefu Li and Shuanghuan Lv and Xiaofeng Wu and Xiaotian Zhuang},
booktitle = {ICASSP 2024},
year = {2024}
}