{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,23]],"date-time":"2026-07-23T19:47:25Z","timestamp":1784836045418,"version":"3.55.0"},"reference-count":46,"publisher":"MDPI AG","issue":"20","license":[{"start":{"date-parts":[[2023,10,10]],"date-time":"2023-10-10T00:00:00Z","timestamp":1696896000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Natural Science Foundation of China","award":["U1803261"],"award-info":[{"award-number":["U1803261"]}]},{"name":"National Natural Science Foundation of China","award":["2022D01C58"],"award-info":[{"award-number":["2022D01C58"]}]},{"name":"National Natural Science Foundation of China","award":["XJEDU2019Y006"],"award-info":[{"award-number":["XJEDU2019Y006"]}]},{"DOI":"10.13039\/501100015310","name":"Natural Science Foundation of XinJiang","doi-asserted-by":"publisher","award":["U1803261"],"award-info":[{"award-number":["U1803261"]}],"id":[{"id":"10.13039\/501100015310","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100015310","name":"Natural Science Foundation of XinJiang","doi-asserted-by":"publisher","award":["2022D01C58"],"award-info":[{"award-number":["2022D01C58"]}],"id":[{"id":"10.13039\/501100015310","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100015310","name":"Natural Science Foundation of XinJiang","doi-asserted-by":"publisher","award":["XJEDU2019Y006"],"award-info":[{"award-number":["XJEDU2019Y006"]}],"id":[{"id":"10.13039\/501100015310","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Scientific research plan of universities in Xinjiang Uygur Autonomous Region","award":["U1803261"],"award-info":[{"award-number":["U1803261"]}]},{"name":"Scientific research plan of universities in Xinjiang Uygur Autonomous Region","award":["2022D01C58"],"award-info":[{"award-number":["2022D01C58"]}]},{"name":"Scientific research plan of universities in Xinjiang Uygur Autonomous Region","award":["XJEDU2019Y006"],"award-info":[{"award-number":["XJEDU2019Y006"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>In recent saliency detection research, too many or too few image features are used in the algorithm, and the processing of saliency map details is not satisfactory, resulting in significant degradation of the salient object detection result. To overcome the above deficiencies and achieve better object detection results, we propose a salient object detection method based on feature optimization by neutrosophic set (NS) theory in this paper. First, prior object knowledge is built using foreground and background models, which include pixel-wise and super-pixel cues. Simultaneously, the feature maps are selected and extracted for feature computation, allowing the object and background features of the image to be separated as much as possible. Second, the salient object is obtained by fusing the features decomposed by the low-rank matrix recovery model with the object prior knowledge. Finally, for salient object detection, we present a novel mathematical description of neutrosophic set theory. To reduce the uncertainty of the obtained saliency map and then obtain good saliency detection results, the new NS theory is proposed. Extensive experiments on five public datasets demonstrate that the results are competitive and superior to previous state-of-the-art methods.<\/jats:p>","DOI":"10.3390\/s23208348","type":"journal-article","created":{"date-parts":[[2023,10,10]],"date-time":"2023-10-10T10:23:42Z","timestamp":1696933422000},"page":"8348","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Salient Object Detection Based on Optimization of Feature Computation by Neutrosophic Set Theory"],"prefix":"10.3390","volume":"23","author":[{"given":"Sensen","family":"Song","sequence":"first","affiliation":[{"name":"Key Laboratory of Signal Detection and Processing, College of Computer Science and Technology, Xinjiang University, Urumqi 830046, China"},{"name":"College of Mathematics and System Science, Xinjiang University, Urumqi 830046, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yue","family":"Li","sequence":"additional","affiliation":[{"name":"Key Laboratory of Signal Detection and Processing, College of Computer Science and Technology, Xinjiang University, Urumqi 830046, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhenhong","family":"Jia","sequence":"additional","affiliation":[{"name":"Key Laboratory of Signal Detection and Processing, College of Computer Science and Technology, Xinjiang University, Urumqi 830046, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1144-6564","authenticated-orcid":false,"given":"Fei","family":"Shi","sequence":"additional","affiliation":[{"name":"Key Laboratory of Signal Detection and Processing, College of Computer Science and Technology, Xinjiang University, Urumqi 830046, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,10,10]]},"reference":[{"key":"ref_1","unstructured":"Palmer, S.E. 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