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Multi-Feature Fusion-GuidedMultiscale Bidirectional Attention Networks for Logistics Pallet Segmentation

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成果类型:
期刊论文
作者:
Cai, Weiwei;Song, Yaping;Duan, Huan;Xia, Zhenwei;Wei, Zhanguo*
通讯作者:
Wei, Zhanguo
作者机构:
[Wei, Zhanguo; Xia, Zhenwei; Song, Yaping; Cai, Weiwei; Duan, Huan] Cent South Univ Forestry & Technol, Sch Logist & Transportat, Changsha 410004, Peoples R China.
[Cai, Weiwei] No Arizona Univ, Grad Sch, Flagstaff, AZ 86011 USA.
通讯机构:
[Wei, Zhanguo] C
Cent South Univ Forestry & Technol, Sch Logist & Transportat, Changsha 410004, Peoples R China.
语种:
英文
关键词:
bidirectional attention mechanism;deep learning;HSV;image segmentation;Logistics pallet segmentation;multi-feature fusion;multiscale network;neural networks
期刊:
工程与科学中的计算机建模(英文)
ISSN:
1526-1492
年:
2022
卷:
131
期:
3
页码:
1539-1555
基金类别:
Funding Statement: This work was supported by the Postgraduate Scientific Research Innovation Project of Hunan Province under Grant QL20210212 and the Scientific Innovation Fund for Postgraduates of Central South University of Forestry and Technology under Grant CX202102043.
机构署名:
本校为第一且通讯机构
院系归属:
交通运输与物流学院
摘要:
In the smart logistics industry, unmanned forklifts that intelligently identify logistics pallets can improve work efficiency in warehousing and transportation and are better than traditional manual forklifts driven by humans. Therefore, they play a critical role in smart warehousing, and semantics segmentation is an effective method to realize the intelligent identification of logistics pallets. However,most current recognition algorithms are ineffective due to the diverse types of pallets, their complex shapes, frequent blockades in productio...

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