{"id":240919,"created":"2025-01-19T01:45:23.172509+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00240919","sets":["6164:6165:6462:11854"]},"path":["11854"],"owner":"11","recid":"240919","title":["各種生成AIモデルに対するAI生成画像検出ツールの性能比較に関する調査研究"],"pubdate":{"attribute_name":"PubDate","attribute_value":"2024-10-15"},"_buckets":{"deposit":"62274e26-b14d-4a03-828a-741dbbbca171"},"_deposit":{"id":"240919","pid":{"type":"depid","value":"240919","revision_id":0},"owners":[11],"status":"published","created_by":11},"item_title":"各種生成AIモデルに対するAI生成画像検出ツールの性能比較に関する調査研究","author_link":["662222","662223","662224","662225"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"各種生成AIモデルに対するAI生成画像検出ツールの性能比較に関する調査研究","subitem_title_language":"ja"},{"subitem_title":"Research Study on Performance Comparison of AI-Generated Image Detection Tools for Various Generated AI Models","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"画像生成AI，AI 画像検出器","subitem_subject_scheme":"Other"}]},"item_type_id":"18","publish_date":"2024-10-15","item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_18_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"京都工芸繊維大学大学院"},{"subitem_text_value":"京都工芸繊維大学"}]},"item_18_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Graduate School of Science and Technology, Kyoto Institute of Technology","subitem_text_language":"en"},{"subitem_text_value":"Kyoto Institute of Technology","subitem_text_language":"en"}]},"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/240919/files/IPSJ-CSS2024173.pdf","label":"IPSJ-CSS2024173.pdf"},"date":[{"dateType":"Available","dateValue":"2026-10-15"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-CSS2024173.pdf","filesize":[{"value":"1.8 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":"30"},{"tax":["include_tax"],"price":"0","billingrole":"46"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"38337f55-bf4c-43ca-9097-ef9471a37530","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2024 by the Information Processing Society of Japan"}]},"item_18_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"井口, 駿治"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"稲葉, 宏幸"}],"nameIdentifiers":[{}]}]},"item_18_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Shunji, Iguchi","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Hiroyuki, Inaba","creatorNameLang":"en"}],"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_18_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"近年，生成AIの急速な発展により様々な商品やサービスが生まれている．その中でも画像生成AIは，画像に関する説明をテキストで与えれば簡単に画像を生成することができるため，急速に普及が進んでいる．しかし，誰でも簡単に画像を生成できる反面，AIを使ったディープフェイクの問題や著作権などの権利侵害のリスクが生じている．そのため，AI生成画像を検出するための手法として，画像に埋め込む電子透かしや機械学習によるAI生成画像検出ツールなど，様々な方法が研究されている．本研究では，機械学習による手法を用いたAI生成画像検出ツールについて，生成AIモデルや画像スタイルの違いが検出精度にどのような影響を及ぼすかを調査する．","subitem_description_type":"Other"}]},"item_18_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"In recent years, the rapid development of generative AI has led to the emergence of various products and services. Among them, image generation AI has gained popularity because it allows users to easily generate images by providing textual descriptions related to the images. However, while it is accessible for anyone to generate images, it also poses risks such as deepfake issues and copyright infringements. Consequently, various methods are being researched to detect AI-generated images, including electronic watermarking embedded in images and machine learning-based detection tools. This study investigates how differences in generative AI models and image styles affect the detection accuracy of machine learning-based AI-generated image detection tools.","subitem_description_type":"Other"}]},"item_18_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"1299","bibliographic_titles":[{"bibliographic_title":"コンピュータセキュリティシンポジウム2024論文集"}],"bibliographicPageStart":"1295","bibliographicIssueDates":{"bibliographicIssueDate":"2024-10-15","bibliographicIssueDateType":"Issued"}}]},"relation_version_is_last":true,"weko_creator_id":"11"},"updated":"2025-03-06T05:56:50.409489+00:00","links":{}}