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dc.contributor.author최용석-
dc.date.accessioned2021-09-08T07:24:22Z-
dc.date.available2021-09-08T07:24:22Z-
dc.date.issued2020-03-
dc.identifier.citationSAC '20: Proceedings of the 35th Annual ACM Symposium on Applied Computing, Page. 1096-1103en_US
dc.identifier.isbn978-1-4503-6866-7-
dc.identifier.urihttps://dl.acm.org/doi/10.1145/3341105.3373931-
dc.identifier.urihttps://repository.hanyang.ac.kr/handle/20.500.11754/164982-
dc.description.abstractThe objective of Zero-Shot Learning (ZSL) is to classify the class labels of unseen objects using external knowledge representing semantic information. Traditional zero-shot recognition models have the limitation that they rely only on the visual appearance of an unseen object. To alleviate this limitation, we propose a novel method that calibrates the visual prediction of an unseen object by using contextual information based on similarities between the unseen object and its surrounding seen objects in a multi-object scene. We incorporate the proposed method into each of the traditional models and conduct a comparative evaluation between the models with and without our calibration algorithm. The evaluation results show consistent performance improvements by a significant margin.en_US
dc.description.sponsorshipThis work was supported by the National Research Foundation of Korea (NRF), a grant funded by the Korean government (Ministry of Science and ICT) (2018R1A5A7059549), the ITRC (Information Technology Research Center) support program (IITP-2017-0-01642) supervised by the IITP (Institute for Information and communications Technology Promotion, Korea), and the Technology Innovation Program (10077553) funded by the Ministry of Trade, Industry, and Energy (MOTIE, Korea).en_US
dc.language.isoenen_US
dc.publisherACMen_US
dc.subjectZero-shot learningen_US
dc.subjectsimilarity-based calibrationen_US
dc.subjectsemantic embeddingen_US
dc.subjectknowledge graphen_US
dc.titleSimilarity-based Calibration Method for Zero-Shot Recognition in Multi-object Scenesen_US
dc.typeArticleen_US
dc.identifier.doi10.1145/3341105.3373931-
dc.relation.page1096-1103-
dc.contributor.googleauthorChang, Doo Soo-
dc.contributor.googleauthorCho, Gun Hee-
dc.contributor.googleauthorChoi, Yong Suk-
dc.relation.code20200164-
dc.sector.campusS-
dc.sector.daehakCOLLEGE OF ENGINEERING[S]-
dc.sector.departmentDEPARTMENT OF COMPUTER SCIENCE-
dc.identifier.pidcys-
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COLLEGE OF ENGINEERING[S](공과대학) > COMPUTER SCIENCE(컴퓨터소프트웨어학부) > Articles
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