{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00237356","sets":["1164:1384:11463:11665"]},"path":["11665"],"owner":"44499","recid":"237356","title":["CNNモデルの内部活性化状態を用いた 訓練データセットのデバックとテスティング"],"pubdate":{"attribute_name":"公開日","attribute_value":"2024-07-18"},"_buckets":{"deposit":"86868273-3d4d-4c82-92ec-456343c05ec6"},"_deposit":{"id":"237356","pid":{"type":"depid","value":"237356","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"CNNモデルの内部活性化状態を用いた 訓練データセットのデバックとテスティング","author_link":["649791","649789","649790","649785","649784","649786","649783","649787","649792","649788"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"CNNモデルの内部活性化状態を用いた 訓練データセットのデバックとテスティング"},{"subitem_title":"Debugging and testing of training datasets using internal activation states of CNN models","subitem_title_language":"en"}]},"item_type_id":"4","publish_date":"2024-07-18","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"信州大学工学部"},{"subitem_text_value":"信州大学大学院総合理工学研究科"},{"subitem_text_value":"信州大学工学部"},{"subitem_text_value":"信州大学工学部"},{"subitem_text_value":"国立情報学研究所"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Sinshu University","subitem_text_language":"en"},{"subitem_text_value":"Graduate School of Science and Engineering Sinshu University","subitem_text_language":"en"},{"subitem_text_value":"Sinshu University","subitem_text_language":"en"},{"subitem_text_value":"Sinshu University::National Institute of Informatics","subitem_text_language":"en"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"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/237356/files/IPSJ-SE24217002.pdf","label":"IPSJ-SE24217002.pdf"},"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-SE24217002.pdf","filesize":[{"value":"2.4 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"0","billingrole":"12"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_login","version_id":"742aa8eb-dcbf-4e26-8c20-9ddf11e8cffe","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2024 by the Institute of Electronics, Information and Communication Engineers This SIG report is only available to those in membership of the SIG."}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"大渕, 大地"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"勝家, 拓巳"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"岡野, 浩三"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"小形, 真平"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"中島, 震"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Daichi, Ofuchi","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Takumi, Katsuie","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Kozo, Okano","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Shinpei, Ogata","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Shin, Nakajima","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN10112981","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":"2188-8825","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"近年，人工知能 (AI) や機械学習の技術は様々な分野で成果をあげている．AI ソフトウェアをシステムに組み込むうえで，AI ソフトウェアの品質が重要視されている．NN モデルに対し，追加の訓練データセットのニューロンカバレッジ (NC) を計算し，その結果に基づいて外れ値の検出を行い，その外れ値を除去することでモデルの品質，特にロバスト性が向上する追加訓練データセットのデバッグ方法が知られている．そこで，本稿では先行研究の実験を CNN モデルに拡張し，CNN モデルでも先行研究と同じような成果を確認した．また，先行研究の手法を用いてロバスト性を維持したまま，正確性を向上するような追加訓練データを構築できることを確認した．","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"Recently, Artificial Intelligence (AI) and machine learning technologies have made great achievements in various fields. The quality of AI software has become an important issue in integrating AI software into systems. There is a well-known method for debugging additional training datasets which improves the quality, especially robustness, of the model by calculating the Neuronal Coverage (NC) of the additional training datasets for the NN model, detecting outliers based on the results, and removing them. Therefore, in this paper, we extend the experiments of the previous study to CNN models and confirm the same results as in the previous study. We also confirmed that it is possible to construct an additional training dataset that improves the accuracy while maintaining the robustness using the method of the previous study.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"6","bibliographic_titles":[{"bibliographic_title":"研究報告ソフトウェア工学（SE）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2024-07-18","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"2","bibliographicVolumeNumber":"2024-SE-217"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":237356,"updated":"2025-01-19T08:54:44.042739+00:00","links":{},"created":"2025-01-19T01:39:56.533013+00:00"}