Learning to Count Arbitrary Industrial Manufacturing Workpieces-Reference-Cited by-同舟云学术

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Learning to Count Arbitrary Industrial Manufacturing Workpieces

Published:2024-05 Issue:5 Volume:20 Page:7719-7731
ISSN:1551-3203
Container-title:IEEE Transactions on Industrial Informatics
language:
Short-container-title:IEEE Trans. Ind. Inf.

Author:

Jiang Ziyi¹^ORCID,Zhai Yikui¹^ORCID,Ke Feng²^ORCID,Zhou Jianhong¹^ORCID,Genovese Angelo³^ORCID,Piuri Vincenzo³^ORCID,Scotti Fabio³^ORCID

Affiliation:

1. School of Electronics and Information Engineering, Wuyi University, Jiangmen, China

2. School of Electronic and Information Engineering, South China University of Technology, Guangzhou, China

3. Departimento di Information, Universita, Degli Studi di Milano, Milano, Italy

Funder

Basic and Applied Basic Research Foundation of Guangdong Province

Guangdong Science and Technology Planning

Guangdong Higher Education Innovation and Strengthening School

Wuyi University Hong Kong and Macao Joint Research and Development Fund

Guangdong Jiangmen Science and Technology Research

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/9424/10521545/10444692.pdf?arnumber=10444692

Reference47 articles.

1. Deep learning

2. A Circular Target Feature Detection Framework Based on DCNN for Industrial Applications

3. PLC Past Linear Temporal Logic for Monitoring Applications in Industrial Control Systems

4. A Fast Quantity and Position Detection Method Based on Monocular Vision for a Workpieces Counting and Sorting System

5. NILM Dashboard: A Power System Monitor for Electromechanical Equipment Diagnostics

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