{"created":"2023-11-13T07:47:42.683665+00:00","id":2000253,"links":{},"metadata":{"_buckets":{"deposit":"b66d4f56-5fe2-433e-87f2-803933260fdf"},"_deposit":{"created_by":14,"id":"2000253","owner":"14","owners":[14],"pid":{"revision_id":0,"type":"depid","value":"2000253"},"status":"published"},"_oai":{"id":"oai:kyutech.repo.nii.ac.jp:02000253","sets":["15:20"]},"author_link":["23300"],"control_number":"2000253","item_23_biblio_info_6":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2022-09","bibliographicIssueDateType":"Issued"},"bibliographicPageStart":"CH-011"}]},"item_23_description_4":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"ガウス過程回帰を用いて深度画像の欠損部分の深度値予測を行う手法を提案する.セマンティックセグメンテーションを用いてRGB画像のピクセルのカテゴリ尤度を抽出し,それに位置情報を加えた特徴量空間上でガウス過程回帰による深度推定を行った.その際,カテゴリの尤度における不確実性を考慮するために,共分散行列にペナルティ項を導入した.この提案手法を一般化することによって,説明変数の観測ノイズを考慮するガウス過程回帰を導くことができた.この一般化した手法は,全ての入力データを等価に扱わず,入力データに不確実性に基づいた優劣をつけて回帰を行うと思われ,汎用性が高い手法という結論を得た.","subitem_description_language":"ja","subitem_description_type":"Abstract"}]},"item_23_description_5":{"attribute_name":"備考","attribute_value_mlt":[{"subitem_description":"第21回情報科学技術フォーラム, FIT2022, 2022年9月13日-15日, 慶應義塾大学矢上キャンパス","subitem_description_language":"ja","subitem_description_type":"Other"}]},"item_23_rights_13":{"attribute_name":"著作権関連情報","attribute_value_mlt":[{"subitem_rights":"Copyright (c) 2022 by The Institute of Electronics, Information and Communication Engineers and Information Processing Society of Japan All rights reserved."}]},"item_23_select_59":{"attribute_name":"査読の有無","attribute_value_mlt":[{"subitem_select_item":"no"}]},"item_23_version_type_58":{"attribute_name":"出版タイプ","attribute_value_mlt":[{"subitem_version_resource":"http://purl.org/coar/version/c_970fb48d4fbd8a85","subitem_version_type":"VoR"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"梅田, 裕輔","creatorNameLang":"ja"},{"creatorName":"Umeda, Yusuke","creatorNameLang":"en"}]},{"creatorNames":[{"creatorName":"Hanazawa, Akitoshi","creatorNameLang":"en"},{"creatorName":"花沢, 明俊","creatorNameLang":"ja"}],"familyNames":[{},{}],"givenNames":[{},{}],"nameIdentifiers":[{},{},{},{}]}]},"item_files":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_access","date":[{"dateType":"Available","dateValue":"2023-11-13"}],"filename":"LaSEINE-2022_DC08_4.pdf","filesize":[{"value":"946 KB"}],"format":"application/pdf","mimetype":"application/pdf","url":{"url":"https://kyutech.repo.nii.ac.jp/record/2000253/files/LaSEINE-2022_DC08_4.pdf"},"version_id":"dccefeda-782d-455e-8bd4-9cae969cb393"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourcetype":"conference paper","resourceuri":"http://purl.org/coar/resource_type/c_5794"}]},"item_title":"セグメンテーションおよびガウス過程回帰による深度画像の欠損値予測とその一般化","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"セグメンテーションおよびガウス過程回帰による深度画像の欠損値予測とその一般化","subitem_title_language":"ja"}]},"item_type_id":"23","owner":"14","path":["20"],"pubdate":{"attribute_name":"PubDate","attribute_value":"2023-11-13"},"publish_date":"2023-11-13","publish_status":"0","recid":"2000253","relation_version_is_last":true,"title":["セグメンテーションおよびガウス過程回帰による深度画像の欠損値予測とその一般化"],"weko_creator_id":"14","weko_shared_id":-1},"updated":"2023-11-13T07:53:05.955628+00:00"}