{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,4]],"date-time":"2026-02-04T00:10:20Z","timestamp":1770163820576,"version":"3.49.0"},"reference-count":15,"publisher":"SAGE Publications","issue":"4","license":[{"start":{"date-parts":[[2020,1,27]],"date-time":"2020-01-27T00:00:00Z","timestamp":1580083200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Journal of Intelligent &amp; Fuzzy Systems"],"published-print":{"date-parts":[[2020,4,30]]},"abstract":"<jats:p>In view of the objectively ambiguous feature of infrared image of unmanned autonomous ship, this paper presents a quantitative method to deal with the ambiguity problem in infrared image by using the fuzzy mathematical model to realize the purpose of intelligent recognition of infrared imaging target. In order to simplify the computation of target recognition and improve the response time and accuracy in the selection of target features in infrared images, three features of target location, radiation distribution and shape are selected for analysis in this paper. The membership functions of these three features are weighted to calculate the confidence, and the classification and recognition are realized according to the confidence. Finally, the simulation results show that the recognition method proposed in this paper can effectively identify the target, and the recognition rate is very high. Compared with the recognition methods based on neural network and SVM, the recognition distance of this method is longer than that of the latter two methods.<\/jats:p>","DOI":"10.3233\/jifs-179623","type":"journal-article","created":{"date-parts":[[2020,1,28]],"date-time":"2020-01-28T16:24:20Z","timestamp":1580228660000},"page":"3981-3989","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":5,"title":["Intelligent recognition method of infrared imaging target of unmanned autonomous ship based on fuzzy mathematical model"],"prefix":"10.1177","volume":"38","author":[{"given":"Renqiang","family":"Wang","sequence":"first","affiliation":[{"name":"Navigation College, Jiangsu Maritime Institute, Gezhi Road, Jiangning District, Nanjing, China"}]},{"given":"Keyin","family":"Miao","sequence":"additional","affiliation":[{"name":"Navigation College, Jiangsu Maritime Institute, Gezhi Road, Jiangning District, Nanjing, China"}]},{"given":"Jianming","family":"Sun","sequence":"additional","affiliation":[{"name":"Navigation College, Jiangsu Maritime Institute, Gezhi Road, Jiangning District, Nanjing, China"}]}],"member":"179","published-online":{"date-parts":[[2020,1,27]]},"reference":[{"issue":"2","key":"e_1_3_2_2_2","first-page":"1","article-title":"Research summary of unmanned ship","volume":"43","author":"Gao ZJ.","year":"2017","unstructured":"GaoZJ., ZhangYJ., SunPT. and LiWH., Research summary of unmanned ship, Dalian Haishi Daxue Xuebao\/Journal of Dalian Maritime University 43(2) (2017), 1\u20137.","journal-title":"Dalian Haishi Daxue Xuebao\/Journal of Dalian Maritime University"},{"key":"e_1_3_2_3_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11071-015-2248-1"},{"issue":"07","key":"e_1_3_2_4_2","first-page":"160","article-title":"Infrared ship target detection method based on deep convolution neural network","volume":"436","author":"Wenxiu W.","year":"2018","unstructured":"WenxiuW., YutianF., FengD. and FengL., Infrared ship target detection method based on deep convolution neural network, Journal of Optics 436(07) (2018), 160\u2013166.","journal-title":"Journal of Optics"},{"issue":"1","key":"e_1_3_2_5_2","first-page":"167","article-title":"Infrared ship target recognition based on svm classification","volume":"45","author":"Difei Z.","year":"2016","unstructured":"DifeiZ., JinsuoZ., KemingY., MingweiC. and YongguoW., Infrared ship target recognition based on svm classification, Infrared and Laser Engineering 45(1) (2016), 167\u2013172.","journal-title":"Infrared and Laser Engineering"},{"key":"e_1_3_2_6_2","doi-asserted-by":"publisher","DOI":"10.1111\/vsu.12372"},{"key":"e_1_3_2_7_2","doi-asserted-by":"publisher","DOI":"10.1039\/C6AN02048H"},{"key":"e_1_3_2_8_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.apm.2014.10.006"},{"issue":"3","key":"e_1_3_2_9_2","first-page":"393","article-title":"Evaluation of collection methods in reverse logistics by using fuzzy mathematics, Benchmarking:","volume":"22","author":"Jindal A.","year":"2015","unstructured":"JindalA. and SangwanKS., Evaluation of collection methods in reverse logistics by using fuzzy mathematics, Benchmarking:, An International Journal 22(3) (2015), 393\u2013410.","journal-title":"An International Journal"},{"issue":"5","key":"e_1_3_2_10_2","first-page":"946","article-title":"Gis and fuzzy mathematics-based chemical components usability of flue-cured tobacco leaves evaluation for strong-flavor type flue-cured tobacco in hunan","volume":"29","author":"Wei LI.","year":"2015","unstructured":"WeiLI., XiaohuaD., QingmingZ., ChunshengX., KaiZ. and UniversityHA., Gis and fuzzy mathematics-based chemical components usability of flue-cured tobacco leaves evaluation for strong-flavor type flue-cured tobacco in hunan, Journal of Nuclear Agricultural Sciences 29(5) (2015), 946\u2013953.","journal-title":"Journal of Nuclear Agricultural Sciences"},{"key":"e_1_3_2_11_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11771-015-2604-9"},{"key":"e_1_3_2_12_2","doi-asserted-by":"publisher","DOI":"10.4236\/gep.2014.22005"},{"key":"e_1_3_2_13_2","doi-asserted-by":"publisher","DOI":"10.1002\/sec.905"},{"key":"e_1_3_2_14_2","doi-asserted-by":"publisher","DOI":"10.1111\/ijfs.13280"},{"key":"e_1_3_2_15_2","doi-asserted-by":"publisher","DOI":"10.1111\/jtxs.12141"},{"issue":"2","key":"e_1_3_2_16_2","first-page":"30","article-title":"Research on evaluation method of simulation of infrared imaging sensor based on structural similarity and fidelity","volume":"36","author":"Shu-Li L.","year":"2015","unstructured":"Shu-LiL., Yan-LiH., Jian-CunR. and Zhao-LongLI., Research on evaluation method of simulation of infrared imaging sensor based on structural similarity and fidelity, Infra-red 36(2) (2015), 30\u201335.","journal-title":"Infra-red"}],"container-title":["Journal of Intelligent &amp; 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