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Image Classification Method Based on Multi-Agent Reinforcement Learning for Defects Detection for Casting
A casting image classification method based on multi-agent reinforcement learning is proposed in this paper to solve the problem of casting defects detection. To reduce the detection time, each agent observes only a small part of the image and can move freely on the image to judge the result togethe...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9323396/ https://www.ncbi.nlm.nih.gov/pubmed/35890824 http://dx.doi.org/10.3390/s22145143 |
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author | Liu, Chaoyue Zhang, Yulai Mao, Sijia |
author_facet | Liu, Chaoyue Zhang, Yulai Mao, Sijia |
author_sort | Liu, Chaoyue |
collection | PubMed |
description | A casting image classification method based on multi-agent reinforcement learning is proposed in this paper to solve the problem of casting defects detection. To reduce the detection time, each agent observes only a small part of the image and can move freely on the image to judge the result together. In the proposed method, the convolutional neural network is used to extract the local observation features, and the hidden state of the gated recurrent unit is used for message transmission between different agents. Each agent acts in a decentralized manner based on its own observations. All agents work together to determine the image type and update the parameters of the models by the stochastic gradient descent method. The new method maintains high accuracy. Meanwhile, the computational time can be significantly reduced to only one fifth of that of the GhostNet. |
format | Online Article Text |
id | pubmed-9323396 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-93233962022-07-27 Image Classification Method Based on Multi-Agent Reinforcement Learning for Defects Detection for Casting Liu, Chaoyue Zhang, Yulai Mao, Sijia Sensors (Basel) Article A casting image classification method based on multi-agent reinforcement learning is proposed in this paper to solve the problem of casting defects detection. To reduce the detection time, each agent observes only a small part of the image and can move freely on the image to judge the result together. In the proposed method, the convolutional neural network is used to extract the local observation features, and the hidden state of the gated recurrent unit is used for message transmission between different agents. Each agent acts in a decentralized manner based on its own observations. All agents work together to determine the image type and update the parameters of the models by the stochastic gradient descent method. The new method maintains high accuracy. Meanwhile, the computational time can be significantly reduced to only one fifth of that of the GhostNet. MDPI 2022-07-08 /pmc/articles/PMC9323396/ /pubmed/35890824 http://dx.doi.org/10.3390/s22145143 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Liu, Chaoyue Zhang, Yulai Mao, Sijia Image Classification Method Based on Multi-Agent Reinforcement Learning for Defects Detection for Casting |
title | Image Classification Method Based on Multi-Agent Reinforcement Learning for Defects Detection for Casting |
title_full | Image Classification Method Based on Multi-Agent Reinforcement Learning for Defects Detection for Casting |
title_fullStr | Image Classification Method Based on Multi-Agent Reinforcement Learning for Defects Detection for Casting |
title_full_unstemmed | Image Classification Method Based on Multi-Agent Reinforcement Learning for Defects Detection for Casting |
title_short | Image Classification Method Based on Multi-Agent Reinforcement Learning for Defects Detection for Casting |
title_sort | image classification method based on multi-agent reinforcement learning for defects detection for casting |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9323396/ https://www.ncbi.nlm.nih.gov/pubmed/35890824 http://dx.doi.org/10.3390/s22145143 |
work_keys_str_mv | AT liuchaoyue imageclassificationmethodbasedonmultiagentreinforcementlearningfordefectsdetectionforcasting AT zhangyulai imageclassificationmethodbasedonmultiagentreinforcementlearningfordefectsdetectionforcasting AT maosijia imageclassificationmethodbasedonmultiagentreinforcementlearningfordefectsdetectionforcasting |