{"id":151498,"date":"2000-10-01T00:00:00","date_gmt":"2000-10-01T00:00:00","guid":{"rendered":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/msr-research-item\/ifind-a-system-for-semantics-and-feature-based-image-retrieval-over-internet\/"},"modified":"2018-10-16T20:57:52","modified_gmt":"2018-10-17T03:57:52","slug":"ifind-a-system-for-semantics-and-feature-based-image-retrieval-over-internet","status":"publish","type":"msr-research-item","link":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/publication\/ifind-a-system-for-semantics-and-feature-based-image-retrieval-over-internet\/","title":{"rendered":"iFind&#8221;\u201dA System for Semantics and Feature Based Image Retrieval over Internet"},"content":{"rendered":"<div class=\"asset-content\">\n<p>iFind\u00a9 (v1.0) is a web based image retrieval system developed at Microsoft Research China. It provides the functionalities of keyword based image search, query by image example, category based image browsing, relevance feedback, and semi-automatic image annotation. The key technology in the system is the integrated semantics and feature based image retrieval and relevance feedback approach, which will be presented in our paper in the ACM Multimedia 2000 Proceedings [1]. When the user provides feedback images, the system can refine the retrieval result based on the user\u2019s feedback. In the meantime, the system updates the annotation of feedback images by increasing the linkage to the positive examples\u2019 annotation and decreasing the linkage to the negative examples\u2019 annotation. The updated annotation can further help to improve image retrieval results of the system in later use.<\/p>\n<\/div>\n<p><!-- .asset-content --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>iFind\u00a9 (v1.0) is a web based image retrieval system developed at Microsoft Research China. It provides the functionalities of keyword based image search, query by image example, category based image browsing, relevance feedback, and semi-automatic image annotation. The key technology in the system is the integrated semantics and feature based image retrieval and relevance feedback [&hellip;]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","msr-author-ordering":null,"msr_publishername":"Association for Computing Machinery, Inc.","msr_publisher_other":"","msr_booktitle":"","msr_chapter":"","msr_edition":"","msr_editors":"","msr_how_published":"","msr_isbn":"","msr_issue":"","msr_journal":"","msr_number":"","msr_organization":"","msr_pages_string":"","msr_page_range_start":"","msr_page_range_end":"","msr_series":"","msr_volume":"","msr_copyright":"Copyright \u00a9 2000 by the Association for Computing Machinery, Inc. Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, to republish, to post on servers, or to redistribute to lists, requires prior specific permission and\/or a fee. Request permissions from Publications Dept, ACM Inc., fax +1 (212) 869-0481, or permissions@acm.org. The definitive version of this paper can be found at ACM's Digital Library -http:\/\/www.acm.org\/dl\/.","msr_conference_name":"","msr_doi":"","msr_arxiv_id":"","msr_s2_paper_id":"","msr_mag_id":"","msr_pubmed_id":"","msr_other_authors":"HongJiang Zhang, Chunhui Hu, Wenyin 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