{"created":"2023-06-19T10:29:55.531068+00:00","id":10009,"links":{},"metadata":{"_buckets":{"deposit":"c9eeb6c3-f378-4ca5-9f4d-3d8708bf3a7d"},"_deposit":{"created_by":18,"id":"10009","owners":[18],"pid":{"revision_id":0,"type":"depid","value":"10009"},"status":"published"},"_oai":{"id":"oai:muroran-it.repo.nii.ac.jp:00010009","sets":["216:316","216:352","46"]},"author_link":["21131","39157","54988"],"item_79_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2018-06-01","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"10","bibliographicPageEnd":"4673","bibliographicPageStart":"4665","bibliographicVolumeNumber":"14","bibliographic_titles":[{"bibliographic_title":"IEEE Transactions on Industrial Informatics","bibliographic_titleLang":"en"}]}]},"item_79_description_23":{"attribute_name":"フォーマット","attribute_value_mlt":[{"subitem_description":"application/pdf","subitem_description_type":"Other"}]},"item_79_description_7":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"With the rapid development of Internet of things devices and network infrastructure, there have been a lot of sensors adopted in the industrial productions, resulting in a large size of data. One of the most popular examples is the manufacture inspection, which is to detect the defects of the products. In order to implement a robust inspection system with higher accuracy, we propose a deep learning based classification model in this paper, which can find the possible defective products. As there may be many assembly lines in one factory, one huge problem in this scenario is how to process such big data in real time. Therefore, we design our system with the concept of fog computing. By offloading the computation burden from the central server to the fog nodes, the system obtains the ability to deal with extremely large data. There are two obvious advantages in our system. The first one is that we adapt the convolutional neural network model to the fog computing environment, which significantly improves its computing efficiency. The other one is that we work out an inspection model, which can simultaneously indicate the defect type and its degree. The experiments well prove that the proposed method is robust and efficient.","subitem_description_language":"en","subitem_description_type":"Abstract"}]},"item_79_link_17":{"attribute_name":"出版者版へのリンク","attribute_value_mlt":[{"subitem_link_text":"10.1109/TII.2018.2842821","subitem_link_url":"https://doi.org/10.1109/TII.2018.2842821"}]},"item_79_link_5":{"attribute_name":"室蘭工業大学研究者データベースへのリンク","attribute_value_mlt":[{"subitem_link_text":"太田 香（OTA Kaoru）","subitem_link_url":"http://rdsoran.muroran-it.ac.jp/html/100000140_ja.html"},{"subitem_link_text":"董 冕雄（DONG Mianxiong）","subitem_link_url":"http://rdsoran.muroran-it.ac.jp/html/100000145_ja.html"}]},"item_79_publisher_11":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"IEEE","subitem_publisher_language":"en"}]},"item_79_relation_18":{"attribute_name":"DOI","attribute_value_mlt":[{"subitem_relation_type":"isVersionOf","subitem_relation_type_id":{"subitem_relation_type_id_text":"10.1109/TII.2018.2842821","subitem_relation_type_select":"DOI"}}]},"item_79_rights_19":{"attribute_name":"権利","attribute_value_mlt":[{"subitem_rights":"© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.","subitem_rights_language":"en"}]},"item_79_source_id_12":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"1551-3203","subitem_source_identifier_type":"PISSN"}]},"item_79_source_id_14":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA12023428","subitem_source_identifier_type":"NCID"}]},"item_79_subject_9":{"attribute_name":"日本十進分類法","attribute_value_mlt":[{"subitem_subject":"007","subitem_subject_scheme":"NDC"}]},"item_79_version_type_21":{"attribute_name":"著者版フラグ","attribute_value_mlt":[{"subitem_version_resource":"http://purl.org/coar/version/c_ab4af688f83e57aa","subitem_version_type":"AM"}]},"item_access_right":{"attribute_name":"アクセス権","attribute_value_mlt":[{"subitem_access_right":"open access","subitem_access_right_uri":"http://purl.org/coar/access_right/c_abf2"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorAffiliations":[{"affiliationNameIdentifiers":[],"affiliationNames":[{"affiliationName":""}]}],"creatorNames":[{"creatorName":"LI, Liangzhi","creatorNameLang":"en"},{"creatorName":"李, 良知","creatorNameLang":"ja"}],"familyNames":[{},{}],"givenNames":[{},{}],"nameIdentifiers":[{}]},{"creatorAffiliations":[{"affiliationNameIdentifiers":[{}],"affiliationNames":[{},{}]}],"creatorNames":[{"creatorName":"OTA,  Kaoru","creatorNameLang":"en"},{"creatorName":"太田, 香","creatorNameLang":"ja"},{"creatorName":"オオタ, カオル","creatorNameLang":"ja-Kana"}],"familyNames":[{},{},{}],"givenNames":[{},{},{}],"nameIdentifiers":[{},{}]},{"creatorAffiliations":[{"affiliationNameIdentifiers":[{}],"affiliationNames":[{},{}]}],"creatorNames":[{"creatorName":"DONG,  Mianxiong","creatorNameLang":"en"},{"creatorName":"トウ, メンユウ","creatorNameLang":"ja-Kana"},{"creatorName":"董, 冕雄","creatorNameLang":"ja"}],"familyNames":[{},{},{}],"givenNames":[{},{},{}],"nameIdentifiers":[{},{}]}]},"item_files":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_date","date":[{"dateType":"Available","dateValue":"2019-07-16"}],"displaytype":"detail","filename":"IEEETII_14_10_4665_4673.pdf","filesize":[{"value":"577.4 kB"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"label":"IEEETII_14_10_4665_4673","objectType":"fulltext","url":"https://muroran-it.repo.nii.ac.jp/record/10009/files/IEEETII_14_10_4665_4673.pdf"},"version_id":"107c9afd-2805-4641-a97d-0222d6098c54"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"Fog computing","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"manufacture inspection","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"smart industry","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"deep learning","subitem_subject_language":"en","subitem_subject_scheme":"Other"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"eng"}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourcetype":"journal article","resourceuri":"http://purl.org/coar/resource_type/c_6501"}]},"item_title":"Deep Learning for Smart Industry:Efficient Manufacture Inspection Systemwith Fog Computing","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Deep Learning for Smart Industry:Efficient Manufacture Inspection Systemwith Fog Computing","subitem_title_language":"en"}]},"item_type_id":"79","owner":"18","path":["46","316","352"],"pubdate":{"attribute_name":"PubDate","attribute_value":"2019-07-16"},"publish_date":"2019-07-16","publish_status":"0","recid":"10009","relation_version_is_last":true,"title":["Deep Learning for Smart Industry:Efficient Manufacture Inspection Systemwith Fog Computing"],"weko_creator_id":"18","weko_shared_id":-1},"updated":"2023-12-15T02:02:16.908130+00:00"}