{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,11]],"date-time":"2025-11-11T13:31:34Z","timestamp":1762867894578,"version":"build-2065373602"},"reference-count":35,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2019,8,28]],"date-time":"2019-08-28T00:00:00Z","timestamp":1566950400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100002858","name":"China Postdoctoral Science Foundation","doi-asserted-by":"publisher","award":["2014M552479, 2014M552478"],"award-info":[{"award-number":["2014M552479, 2014M552478"]}],"id":[{"id":"10.13039\/501100002858","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Humanities and Social Science Youth Funded Project of Ministry of Education of China","award":["17YJCZH186"],"award-info":[{"award-number":["17YJCZH186"]}]},{"name":"Natural Science Basic Research Plan in Shaanxi Province of China","award":["2013JQ8022"],"award-info":[{"award-number":["2013JQ8022"]}]},{"name":"Scientific Research Project of Education Department of Shaanxi Province","award":["2013JK1181, 2014JK1724"],"award-info":[{"award-number":["2013JK1181, 2014JK1724"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Symmetry"],"abstract":"<jats:p>As a subject area of symmetry, multiple instance learning (MIL) is a special form of a weakly supervised learning problem where the label is related to the bag, not the instances contained in it. The difficulty of MIL lies in the incomplete label information of instances. To resolve this problem, in this paper, we propose a novel diverse density (DD) and multiple part similarity combination method for multiple instance learning, named MILDMS. First, we model the target concepts optimization with a DD function constraint on positive and negative instance space, which can greatly improve the robustness to label noise problem. Next, we combine the positive and negative instances in the bag (generated by hand-crafted and convolutional neural network features) with multiple part similarities to construct an MIL kernel. We evaluate the proposed approach on the MUSK dataset, whose results MUSK1 (91.9%) and MUSK2 (92.2%) show our method is comparable to other MIL algorithms. To further demonstrate generality, we also present experimental results on the PASCAL VOC 2007 and 2012 (46.5% and 42.2%) and COREL (78.6%) that significantly outperforms the state-of-the-art algorithms including deep MIL and other non-deep MIL algorithms.<\/jats:p>","DOI":"10.3390\/sym11091080","type":"journal-article","created":{"date-parts":[[2019,8,28]],"date-time":"2019-08-28T11:23:18Z","timestamp":1566991398000},"page":"1080","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["MILDMS: Multiple Instance Learning via DD Constraint and Multiple Part Similarity"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3292-6647","authenticated-orcid":false,"given":"Chao","family":"Wen","sequence":"first","affiliation":[{"name":"Research Center for Intelligent Interaction and Information Art, Northwest University, Xi\u2019an 710069, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhan","family":"Li","sequence":"additional","affiliation":[{"name":"Research Center for Intelligent Interaction and Information Art, Northwest University, Xi\u2019an 710069, China"},{"name":"School of Information Science and Technology, Northwest University, Xi\u2019an 710127, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jian","family":"Qu","sequence":"additional","affiliation":[{"name":"Research Center for Intelligent Interaction and Information Art, Northwest University, Xi\u2019an 710069, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qingchen","family":"Fan","sequence":"additional","affiliation":[{"name":"School of Information Science and Technology, Northwest University, Xi\u2019an 710127, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Aiping","family":"Li","sequence":"additional","affiliation":[{"name":"School of Information Science and Technology, Northwest University, Xi\u2019an 710127, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2019,8,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"178","DOI":"10.1016\/j.knosys.2017.11.019","article-title":"A Selective Multiple Instance Transfer Learning Method for Text Categorization Problems","volume":"141","author":"Liu","year":"2018","journal-title":"Knowl. 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