{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00239267","sets":["6164:6165:6522:11751"]},"path":["11751"],"owner":"44499","recid":"239267","title":["画像分類モデルの学習におけるAI生成画像の有効性検討"],"pubdate":{"attribute_name":"公開日","attribute_value":"2024-09-10"},"_buckets":{"deposit":"5c514ec4-3a51-4b23-8e1c-a7f8af6590c9"},"_deposit":{"id":"239267","pid":{"type":"depid","value":"239267","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"画像分類モデルの学習におけるAI生成画像の有効性検討","author_link":["655611","655606","655604","655609","655607","655603","655605","655608","655612","655610"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"画像分類モデルの学習におけるAI生成画像の有効性検討"},{"subitem_title":"Examining Effectiveness of AI-generated Images at a Model Training for Image Classification Tasks","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"データ・機械学習","subitem_subject_scheme":"Other"}]},"item_type_id":"18","publish_date":"2024-09-10","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":"富士通株式会社"},{"subitem_text_value":"株式会社日立製作所"},{"subitem_text_value":"福島キヤノン株式会社"},{"subitem_text_value":"国立情報学研究所"}]},"item_18_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Fujitsu Ltd.","subitem_text_language":"en"},{"subitem_text_value":"Hitachi Ltd.","subitem_text_language":"en"},{"subitem_text_value":"Fukushima Canon Inc.","subitem_text_language":"en"},{"subitem_text_value":"National Institute of Informatics ","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":44499,"item_file_price":{"attribute_name":"Billing file","attribute_type":"file","attribute_value_mlt":[{"url":{"url":"https://ipsj.ixsq.nii.ac.jp/record/239267/files/IPSJ-SES2024039.pdf","label":"IPSJ-SES2024039.pdf"},"date":[{"dateType":"Available","dateValue":"2026-09-10"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-SES2024039.pdf","filesize":[{"value":"1.5 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":"12"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"341c110f-8804-4cce-9103-f5660b3ae9a0","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":"吉井, 章人"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"中道, 拓也"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"佐々木, 瞭太"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"鈴木, 貴大"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"石川, 冬樹"}],"nameIdentifiers":[{}]}]},"item_18_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Akihito, Yoshii","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Takuya, Nnakaichi","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Ryouta, Sasaki","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Takahiro, Suzuki","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Fuyuki, Ishikawa","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":"ディープラーニングによる画像の分類タスクにおいて，ある特定のラベルが付けられた画像が極端に少ないと，特定のクラスの推定結果に差が出ることがある．このような偏り（バイアス）は，実用上においても精度や頑健性だけでなく，倫理的な問題を引き起こす可能性もある．バイアスを是正する方法の一つとして，生成モデルで不足している画像を補うという方法が考えられる．Text-to-image モデルによる生成では，目的の画像をプロンプトにより直感的に生成できるようになってきているが，生成モデルの出力結果にばらつきが生じることもあるため，画像の「良さ」を意識する必要がある．そこで，本研究では，画像のクラス分類におけるクラスごとのサンプル数の偏りが与える精度への影響を是正するために，不足しているクラスの画像を Text-to-image モデルの一つである Stable Diffusion による生成画像で補う手法を検証した．生成モデルが生成した画像を評価する既存指標 (Inception Score, Fréchet Inception Distance) に基づいた条件により画像の「良さ」を定義し，画像の良し悪しが分類モデルの性能に与える影響を比較した．","subitem_description_type":"Other"}]},"item_18_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"Datasets which are used for training of an image classifier model has multiple classes. When each class size is not balanced, the estimation performance of a specific class can be negatively affected because of the small sample size compared to the others (biases). Biases cause not only performance problems but also ethical issues in society; therefore, techniques for debiasing models are needed for dependable classifier models in practical situations. In this research, we formulated experiments to examine a debiasing technique by augmenting an imbalanced dataset by AI-generated images. We examined the “goodness” of AI-generated images by adopting existing measures (Inception Score and Fréchet Inception Distance). Utilizing these criteria, we compared multiple conditions and discussed the results.","subitem_description_type":"Other"}]},"item_18_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"263","bibliographic_titles":[{"bibliographic_title":"ソフトウェアエンジニアリングシンポジウム2024論文集"}],"bibliographicPageStart":"256","bibliographicIssueDates":{"bibliographicIssueDate":"2024-09-10","bibliographicIssueDateType":"Issued"},"bibliographicVolumeNumber":"2024"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":239267,"updated":"2025-01-19T08:06:48.152269+00:00","links":{},"created":"2025-01-19T01:42:48.748244+00:00"}