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MSIA-Net: A Lightweight Infrared Target Detection Network with Efficient Information Fusion
In order to solve the problems of infrared target detection (i.e., the large models and numerous parameters), a lightweight detection network, MSIA-Net, is proposed. Firstly, a feature extraction module named MSIA, which is based on asymmetric convolution, is proposed, and it can greatly reduce the...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10216973/ https://www.ncbi.nlm.nih.gov/pubmed/37238563 http://dx.doi.org/10.3390/e25050808 |
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author | Yu, Jimin Li, Shun Zhou, Shangbo Wang, Hui |
author_facet | Yu, Jimin Li, Shun Zhou, Shangbo Wang, Hui |
author_sort | Yu, Jimin |
collection | PubMed |
description | In order to solve the problems of infrared target detection (i.e., the large models and numerous parameters), a lightweight detection network, MSIA-Net, is proposed. Firstly, a feature extraction module named MSIA, which is based on asymmetric convolution, is proposed, and it can greatly reduce the number of parameters and improve the detection performance by reusing information. In addition, we propose a down-sampling module named DPP to reduce the information loss caused by pooling down-sampling. Finally, we propose a feature fusion structure named LIR-FPN that can shorten the information transmission path and effectively reduce the noise in the process of feature fusion. In order to improve the ability of the network to focus on the target, we introduce coordinate attention (CA) into the LIR-FPN; this integrates the location information of the target into the channel so as to obtain more expressive feature information. Finally, a comparative experiment with other SOTA methods was completed on the FLIR on-board infrared image dataset, which proved the powerful detection performance of MSIA-Net. |
format | Online Article Text |
id | pubmed-10216973 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-102169732023-05-27 MSIA-Net: A Lightweight Infrared Target Detection Network with Efficient Information Fusion Yu, Jimin Li, Shun Zhou, Shangbo Wang, Hui Entropy (Basel) Article In order to solve the problems of infrared target detection (i.e., the large models and numerous parameters), a lightweight detection network, MSIA-Net, is proposed. Firstly, a feature extraction module named MSIA, which is based on asymmetric convolution, is proposed, and it can greatly reduce the number of parameters and improve the detection performance by reusing information. In addition, we propose a down-sampling module named DPP to reduce the information loss caused by pooling down-sampling. Finally, we propose a feature fusion structure named LIR-FPN that can shorten the information transmission path and effectively reduce the noise in the process of feature fusion. In order to improve the ability of the network to focus on the target, we introduce coordinate attention (CA) into the LIR-FPN; this integrates the location information of the target into the channel so as to obtain more expressive feature information. Finally, a comparative experiment with other SOTA methods was completed on the FLIR on-board infrared image dataset, which proved the powerful detection performance of MSIA-Net. MDPI 2023-05-17 /pmc/articles/PMC10216973/ /pubmed/37238563 http://dx.doi.org/10.3390/e25050808 Text en © 2023 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 Yu, Jimin Li, Shun Zhou, Shangbo Wang, Hui MSIA-Net: A Lightweight Infrared Target Detection Network with Efficient Information Fusion |
title | MSIA-Net: A Lightweight Infrared Target Detection Network with Efficient Information Fusion |
title_full | MSIA-Net: A Lightweight Infrared Target Detection Network with Efficient Information Fusion |
title_fullStr | MSIA-Net: A Lightweight Infrared Target Detection Network with Efficient Information Fusion |
title_full_unstemmed | MSIA-Net: A Lightweight Infrared Target Detection Network with Efficient Information Fusion |
title_short | MSIA-Net: A Lightweight Infrared Target Detection Network with Efficient Information Fusion |
title_sort | msia-net: a lightweight infrared target detection network with efficient information fusion |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10216973/ https://www.ncbi.nlm.nih.gov/pubmed/37238563 http://dx.doi.org/10.3390/e25050808 |
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