{"created":"2025-01-19T01:15:41.649130+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00214902","sets":["6504:10735:10808"]},"path":["10808"],"owner":"44499","recid":"214902","title":["CNN 特徴量の列要素 L2 制約とバイナリ化ベクトルを用いた画像検索の性能向上"],"pubdate":{"attribute_name":"公開日","attribute_value":"2021-03-04"},"_buckets":{"deposit":"4399d957-7941-4603-a58d-861e8877b4ca"},"_deposit":{"id":"214902","pid":{"type":"depid","value":"214902","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"CNN 特徴量の列要素 L2 制約とバイナリ化ベクトルを用いた画像検索の性能向上","author_link":["553069","553068","553070"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"CNN 特徴量の列要素 L2 制約とバイナリ化ベクトルを用いた画像検索の性能向上"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"人工知能と認知科学","subitem_subject_scheme":"Other"}]},"item_type_id":"22","publish_date":"2021-03-04","item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_22_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"青学大"},{"subitem_text_value":"青学大"},{"subitem_text_value":"青学大"}]},"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/214902/files/IPSJ-Z83-5N-01.pdf","label":"IPSJ-Z83-5N-01.pdf"},"date":[{"dateType":"Available","dateValue":"2021-12-28"}],"format":"application/pdf","filename":"IPSJ-Z83-5N-01.pdf","filesize":[{"value":"567.4 kB"}],"mimetype":"application/pdf","accessrole":"open_date","version_id":"bb7222b0-372b-412e-81dd-ca1db116e645","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2021 by the Information Processing Society of Japan"}]},"item_22_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"鹿島, 崇"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"鷲見, 和彦"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"金子, 直史"}],"nameIdentifiers":[{}]}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_5794","resourcetype":"conference paper"}]},"item_22_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN00349328","subitem_source_identifier_type":"NCID"}]},"item_22_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"漫画の電子書籍や写真の悪質なアップロードを背景に、電子書籍とそれを撮影し電子化したものなど見かけが違う書籍画像の同一物検索が求められている。ドメインの異なる同一画像でも特徴量が同じになるよう、畳み込みニューラルネットワークの特徴量の列要素にL2制約を導入し、さらに特徴ベクトルのバイナリ化をおこなった。検証として、学習時のクラスに該当しない未使用の漫画ページを、データベース:21760枚、クエリ:522枚で、検索結果のTop-1、Top-5の精度を測定した。ImageNetでプリトレインしたモデルや距離学習、バッチ正規化などの方法と検索精度を比較したところ、提案手法が最高の精度を達成した。","subitem_description_type":"Other"}]},"item_22_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"196","bibliographic_titles":[{"bibliographic_title":"第83回全国大会講演論文集"}],"bibliographicPageStart":"195","bibliographicIssueDates":{"bibliographicIssueDate":"2021-03-04","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"2021"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":214902,"updated":"2025-01-19T16:24:51.437292+00:00","links":{}}