Segmentation Method for Whole Vehicle Wood Detection Based on Improved YOLACT Instance Segmentation Model-Reference-Cited by-同舟云学术

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Segmentation Method for Whole Vehicle Wood Detection Based on Improved YOLACT Instance Segmentation Model

Published:2023 Issue: Volume:11 Page:81434-81448
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Zheng Jishi¹^ORCID,Zheng Junjie²,Zhang Shiwen²^ORCID,Yu Honghui²,Kong Linghua³,Zhigang Ding³

Affiliation:

1. Intelligent Transportation System Research Center, Fujian University of Technology, Fuzhou, China

2. School of Transportation, Fujian University of Technology, Fuzhou, China

3. School of Mechanical and Automotive Engineering, Fujian University of Technology, Fuzhou, China

Funder

School-Enterprise Cooperation Project of Fujian Jinsen Forestry Company Ltd

Forestry Technology Project of Fujian Province

Nature Foundation of Fujian Science and Technology Department

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10198469.pdf?arnumber=10198469

Reference32 articles.

1. Log-End Cut-Area Detection in Images Taken from Rear End of Eucalyptus Timber Trucks

2. Reference Measurement of Roundwood by Fringe Projection

3. A detection approach for bundled log ends based on an improved YOLOv4-Tiny network;cai;Video Eng,2021

4. Application of SSD framework model in detection of logs end

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A Comparative Literature Review of Machine Learning and Image Processing Techniques Used for Scaling and Grading of Wood Logs;Forests;2024-07-17

2. The Impact of Backbone Selection in Yolov8 Models on Brain Tumor Localization;2024

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