Logistics Information Traceability Mechanism of Fresh E-Commerce Based on Image Recognition Technology
Logistics migration and movement require precise information updates for traceability and visibility of goods through E-commerce platforms. Computer vision and digital image processing techniques are used for visual identification and tracking through different warehouses and delivery points. In thi...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2022-01-01
|
| Series: | Applied Bionics and Biomechanics |
| Online Access: | http://dx.doi.org/10.1155/2022/2949216 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832551054484439040 |
|---|---|
| author | Xin Zhang Pengfei Shao |
| author_facet | Xin Zhang Pengfei Shao |
| author_sort | Xin Zhang |
| collection | DOAJ |
| description | Logistics migration and movement require precise information updates for traceability and visibility of goods through E-commerce platforms. Computer vision and digital image processing techniques are used for visual identification and tracking through different warehouses and delivery points. In this article, an incessant visualized tracking scheme (IVTS) is designed for identifying and tracking E-commerce logistics throughout the migration points. This scheme endorsed computer vision technology for logistics recognition and labelled data detection. In this scheme, the labelled logistics data is verified for its similarity in different migrating locations and to the endpoint. Based on the dimensional features and regional-pixel similarity factor, it is verified using the deep neural network. This learning process identifies dimensional variations due to logistics displacement and position suppressing the similarity variations. It is performed based on the migration and information available to prevent tracking errors. For the varying locations and logistics displacement, the error pixel regions are identified and trained for possible similarity detection. The proposed scheme effectively improves visual accuracy, tracking maximization, and logistics detection by reducing dimensional errors. |
| format | Article |
| id | doaj-art-7b462fdb740347ac9f0e8e0693c8a2d7 |
| institution | Kabale University |
| issn | 1754-2103 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Applied Bionics and Biomechanics |
| spelling | doaj-art-7b462fdb740347ac9f0e8e0693c8a2d72025-02-03T06:05:03ZengWileyApplied Bionics and Biomechanics1754-21032022-01-01202210.1155/2022/2949216Logistics Information Traceability Mechanism of Fresh E-Commerce Based on Image Recognition TechnologyXin Zhang0Pengfei Shao1College of BusinessZhejiang Wanli UniversityLogistics migration and movement require precise information updates for traceability and visibility of goods through E-commerce platforms. Computer vision and digital image processing techniques are used for visual identification and tracking through different warehouses and delivery points. In this article, an incessant visualized tracking scheme (IVTS) is designed for identifying and tracking E-commerce logistics throughout the migration points. This scheme endorsed computer vision technology for logistics recognition and labelled data detection. In this scheme, the labelled logistics data is verified for its similarity in different migrating locations and to the endpoint. Based on the dimensional features and regional-pixel similarity factor, it is verified using the deep neural network. This learning process identifies dimensional variations due to logistics displacement and position suppressing the similarity variations. It is performed based on the migration and information available to prevent tracking errors. For the varying locations and logistics displacement, the error pixel regions are identified and trained for possible similarity detection. The proposed scheme effectively improves visual accuracy, tracking maximization, and logistics detection by reducing dimensional errors.http://dx.doi.org/10.1155/2022/2949216 |
| spellingShingle | Xin Zhang Pengfei Shao Logistics Information Traceability Mechanism of Fresh E-Commerce Based on Image Recognition Technology Applied Bionics and Biomechanics |
| title | Logistics Information Traceability Mechanism of Fresh E-Commerce Based on Image Recognition Technology |
| title_full | Logistics Information Traceability Mechanism of Fresh E-Commerce Based on Image Recognition Technology |
| title_fullStr | Logistics Information Traceability Mechanism of Fresh E-Commerce Based on Image Recognition Technology |
| title_full_unstemmed | Logistics Information Traceability Mechanism of Fresh E-Commerce Based on Image Recognition Technology |
| title_short | Logistics Information Traceability Mechanism of Fresh E-Commerce Based on Image Recognition Technology |
| title_sort | logistics information traceability mechanism of fresh e commerce based on image recognition technology |
| url | http://dx.doi.org/10.1155/2022/2949216 |
| work_keys_str_mv | AT xinzhang logisticsinformationtraceabilitymechanismoffreshecommercebasedonimagerecognitiontechnology AT pengfeishao logisticsinformationtraceabilitymechanismoffreshecommercebasedonimagerecognitiontechnology |