{"id":226074,"updated":"2025-01-19T12:35:19.598861+00:00","links":{},"created":"2025-01-19T01:25:33.728805+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00226074","sets":["1164:4061:11136:11254"]},"path":["11254"],"owner":"44499","recid":"226074","title":["Preliminary Investigation of Using SSL for Complex Work Activity Recognition in Industrial Settings"],"pubdate":{"attribute_name":"公開日","attribute_value":"2023-05-17"},"_buckets":{"deposit":"dab9580a-eb47-4908-931d-2fa29bf41d8b"},"_deposit":{"id":"226074","pid":{"type":"depid","value":"226074","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"Preliminary Investigation of Using SSL for Complex Work Activity Recognition in Industrial Settings","author_link":["599519","599521","599527","599523","599522","599518","599526","599524","599525","599520"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Preliminary Investigation of Using SSL for Complex Work Activity Recognition in Industrial Settings"},{"subitem_title":"Preliminary Investigation of Using SSL for Complex Work Activity Recognition in Industrial Settings","subitem_title_language":"en"}]},"item_type_id":"4","publish_date":"2023-05-17","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"Department of Multimedia Engineering, Graduate School of Information Science and Technology, Osaka University"},{"subitem_text_value":"Department of Multimedia Engineering, Graduate School of Information Science and Technology, Osaka University"},{"subitem_text_value":"Department of Multimedia Engineering, Graduate School of Information Science and Technology, Osaka University"},{"subitem_text_value":"Corporate Manufacturing Engineering Center, Toshiba Corporation"},{"subitem_text_value":"Corporate Manufacturing Engineering Center, Toshiba Corporation"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Department of Multimedia Engineering, Graduate School of Information Science and Technology, Osaka University","subitem_text_language":"en"},{"subitem_text_value":"Department of Multimedia Engineering, Graduate School of Information Science and Technology, Osaka University","subitem_text_language":"en"},{"subitem_text_value":"Department of Multimedia Engineering, Graduate School of Information Science and Technology, Osaka University","subitem_text_language":"en"},{"subitem_text_value":"Corporate Manufacturing Engineering Center, Toshiba Corporation","subitem_text_language":"en"},{"subitem_text_value":"Corporate Manufacturing Engineering Center, Toshiba Corporation","subitem_text_language":"en"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"eng"}]},"item_publisher":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"情報処理学会","subitem_publisher_language":"ja"}]},"publish_status":"0","weko_shared_id":-1,"item_file_price":{"attribute_name":"Billing file","attribute_type":"file","attribute_value_mlt":[{"url":{"url":"https://ipsj.ixsq.nii.ac.jp/record/226074/files/IPSJ-UBI23078009.pdf","label":"IPSJ-UBI23078009.pdf"},"date":[{"dateType":"Available","dateValue":"2025-05-17"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-UBI23078009.pdf","filesize":[{"value":"3.7 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"660","billingrole":"5"},{"tax":["include_tax"],"price":"330","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"36"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"a5645dfc-53b7-4508-91b2-033d818c5b79","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2023 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Qingxin, Xia"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Takuya, Maekawa"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Takahiro, Hara"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Hirotomo, Oshima"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Yasuo, Namioka"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Qingxin, Xia","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Takuya, Maekawa","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Takahiro, Hara","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Hirotomo, Oshima","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Yasuo, Namioka","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA11838947","subitem_source_identifier_type":"NCID"}]},"item_4_textarea_12":{"attribute_name":"Notice","attribute_value_mlt":[{"subitem_textarea_value":"SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc."}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_18gh","resourcetype":"technical report"}]},"item_4_source_id_11":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"2188-8698","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"Activity recognition using sensor data collected by wearable sensors has been actively studied in the ubicomp community. However, in industrial settings, (1) labeled sensor data collection is costly and (2) the activities performed by workers are more complex than those of daily activities such as walking and running. This study presents a new self-supervised learning approach that effectively utilizes unlabeled data to improve complex activity recognition performance in industrial domain. In this study, we focus on characteristic actions in each work activity (i.e., operation). We first select sensor data motifs corresponding to the characteristic actions that uniquely and consistently occur in an operation. Then, we calculate the similarity series of the motifs that indicate the occurrence of the motifs in every operation. We train a neural network so that it outputs the reconstructed similarity series, which is helpful in identifying the operations containing the motifs. The trained feature extractor is applied to the downstream task that uses limited labeled data to recognize complex work activities. The proposed approach was evaluated on real-world work activity data and achieved state-of-the-art results.","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"Activity recognition using sensor data collected by wearable sensors has been actively studied in the ubicomp community. However, in industrial settings, (1) labeled sensor data collection is costly and (2) the activities performed by workers are more complex than those of daily activities such as walking and running. This study presents a new self-supervised learning approach that effectively utilizes unlabeled data to improve complex activity recognition performance in industrial domain. In this study, we focus on characteristic actions in each work activity (i.e., operation). We first select sensor data motifs corresponding to the characteristic actions that uniquely and consistently occur in an operation. Then, we calculate the similarity series of the motifs that indicate the occurrence of the motifs in every operation. We train a neural network so that it outputs the reconstructed similarity series, which is helpful in identifying the operations containing the motifs. The trained feature extractor is applied to the downstream task that uses limited labeled data to recognize complex work activities. The proposed approach was evaluated on real-world work activity data and achieved state-of-the-art results.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"8","bibliographic_titles":[{"bibliographic_title":"研究報告ユビキタスコンピューティングシステム（UBI）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2023-05-17","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"9","bibliographicVolumeNumber":"2023-UBI-78"}]},"relation_version_is_last":true,"weko_creator_id":"44499"}}