{"_buckets": {"deposit": "07b7798c-4876-4a09-946d-85f42caf36ad"}, "_deposit": {"id": "11017", "owners": [], "pid": {"revision_id": 0, "type": "depid", "value": "11017"}, "status": "published"}, "_oai": {"id": "oai:nagoya.repo.nii.ac.jp:00011017", "sets": ["314"]}, "author_link": ["33369", "33370", "33371", "33372", "33373"], "item_10_alternative_title_19": {"attribute_name": "その他のタイトル", "attribute_value_mlt": [{"subitem_alternative_title": "A Generative Learning Method for the Recognition of Blurred Characters Taken by Portable Cameras", "subitem_alternative_title_language": "en"}]}, "item_10_biblio_info_6": {"attribute_name": "書誌情報", "attribute_value_mlt": [{"bibliographicIssueDates": {"bibliographicIssueDate": "2006-09-01", "bibliographicIssueDateType": "Issued"}, "bibliographicIssueNumber": "9", "bibliographicPageEnd": "2064", "bibliographicPageStart": "2055", "bibliographicVolumeNumber": "J89-D", "bibliographic_titles": [{"bibliographic_title": "電子情報通信学会論文誌", "bibliographic_titleLang": "ja"}]}]}, "item_10_description_4": {"attribute_name": "抄録", "attribute_value_mlt": [{"subitem_description": "近年,ディジタルカメラ,カメラ付携帯電話が普及しており,それらの機器を用いた文字認識技術の実用化が期待されている.しかし,撮影された画像は低解像度なものになりやすく,更にぼけやぶれなどの影響を受けるため,高精度な認識は難しい.我々の提案する生成型学習法は,人工的に劣化を加えて生成した画像を学習データとすることで,特に携帯ディジタルカメラで問題となる光学的ぼけ,手ぶれ,低解像度化に対処するものである.従来は,学習データを撮影により収集する手法が用いられてきたが,撮影環境が異なるデータに対応するために様々な条件のもとで学習データを収集する必要があり,実用上の難点がある.それに対し本手法は,学習データを原画像から生成するため効率的である.また生成時のパラメータを変化させることで多種の劣化に対応する学習データが生成できる.本手法を用い,実際の劣化を学習に反映させることで,ぼけやぶれを含む低品質文字の認識率が向上することを実験によって示した.", "subitem_description_language": "ja", "subitem_description_type": "Abstract"}]}, "item_10_identifier_60": {"attribute_name": "URI", "attribute_value_mlt": [{"subitem_identifier_type": "HDL", "subitem_identifier_uri": "http://hdl.handle.net/2237/12879"}, {"subitem_identifier_type": "URI", "subitem_identifier_uri": "http://www.ieice.org/jpn/trans_online/index.html"}]}, "item_10_publisher_32": {"attribute_name": "出版者", 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