Automated Scrap Steel Grading via a Hierarchical Learning-Based Framework-Reference-Cited by-同舟云学术

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Automated Scrap Steel Grading via a Hierarchical Learning-Based Framework

Published:2022 Issue: Volume:71 Page:1-13
ISSN:0018-9456
Container-title:IEEE Transactions on Instrumentation and Measurement
language:
Short-container-title:IEEE Trans. Instrum. Meas.

Author:

Tu Qifan¹^ORCID,Li Dawei²^ORCID,Xie Qian³^ORCID,Dai Li¹^ORCID,Wang Jun²^ORCID

Affiliation:

1. College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China

2. College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China

3. Department of Computer Science, University of Oxford, Oxford, U.K

Funder

National Key Research and Development Program of China

Natural Science Foundation of Jiangsu Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/19/9717300/09893213.pdf?arnumber=9893213

Cited by 4 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. An efficient treatment method of scrap intelligent rating based on machine vision;Applied Intelligence;2024-08-31

2. Instance segmentation algorithm for sorting dismantling components of end-of-life vehicles;Engineering Applications of Artificial Intelligence;2024-07

3. FedScrap: Layer-Wise Personalized Federated Learning for Scrap Detection;Electronics;2024-01-28

4. An RGB-D-Based Thickness Feature Descriptor and Its Application on Scrap Steel Grading;IEEE Transactions on Instrumentation and Measurement;2023

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