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Nevertheless, since the overlap of the equipment, the complex background, and the low contrast of the infrared image, the current method still cannot complete the detection and segmentation of the power equipment well. To better segment the power equipment in the infrared image, in this paper, a multispectral instance segmentation (MSIS) based on SOLOv2 is designed, which is an end-to-end and single-stage network. First, we provide a novel structure of multispectral feature extraction, which can simultaneously obtain rich features in visible images and infrared images. Secondly, a module of feature fusion (MARFN) has been constructed to fully obtain fusion features. Finally, the combination of multispectral feature extraction, the module of feature fusion (MARFN), and instance segmentation (SOLOv2) realize multispectral instance segmentation of power equipment. The experimental results show that the proposed MSIS model has an excellent performance in the instance segmentation of power equipment. The MSIS based on ResNet-50 has 40.06% AP.<\/jats:p>","DOI":"10.1155\/2022\/2864717","type":"journal-article","created":{"date-parts":[[2022,1,4]],"date-time":"2022-01-04T17:57:12Z","timestamp":1641319032000},"page":"1-13","source":"Crossref","is-referenced-by-count":23,"title":["MSIS: Multispectral Instance Segmentation Method for Power Equipment"],"prefix":"10.1155","volume":"2022","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7073-6935","authenticated-orcid":true,"given":"Jun","family":"Shu","sequence":"first","affiliation":[{"name":"School of Electrical and Electronic Engineering, Hubei University of Technology, Wuhan 430068, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9721-726X","authenticated-orcid":true,"given":"Juncheng","family":"He","sequence":"additional","affiliation":[{"name":"Hubei Key Laboratory for High-efficiency Utilization of Solar Energy and Operation Control of Energy Storage System, Hubei University of Technology, Wuhan 430068, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8214-239X","authenticated-orcid":true,"given":"Ling","family":"Li","sequence":"additional","affiliation":[{"name":"Hubei Key Laboratory for High-efficiency Utilization of Solar Energy and Operation Control of Energy Storage System, Hubei University of Technology, Wuhan 430068, China"}]}],"member":"311","reference":[{"key":"1","doi-asserted-by":"publisher","DOI":"10.1088\/1755-1315\/714\/4\/042045"},{"key":"2","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1007\/978-3-030-44038-1_1","article-title":"Infrared image fault identification of power equipment based on residual network","volume-title":"Web, Artificial Intelligence and Network Applications","author":"F. 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