{"created":"2023-05-15T11:36:34.385905+00:00","id":205,"links":{},"metadata":{"_buckets":{"deposit":"943d0467-129f-47f5-bb6c-c4f29a54c1bf"},"_deposit":{"created_by":3,"id":"205","owners":[3],"pid":{"revision_id":0,"type":"depid","value":"205"},"status":"published"},"_oai":{"id":"oai:shikoku-u.repo.nii.ac.jp:00000205","sets":["11:154:159"]},"author_link":["369","370"],"item_2_biblio_info_12":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"1995-12-05","bibliographicIssueDateType":"Issued"},"bibliographicPageEnd":"100","bibliographicPageStart":"95","bibliographicVolumeNumber":"1","bibliographic_titles":[{}]}]},"item_2_description_11":{"attribute_name":"抄録(英)","attribute_value_mlt":[{"subitem_description":"In this paper, we propose a pattern classification method for remote sensing data using two neural networks; one (NN1) is trained by a back-propagation method and another (NN2) by self-organized feature mapping and knowledge-based processing. The NN1 has the ability to recognize complex patterns and classify them. However, it has two disadvantages : it may misclassify the patterns, and it is difficult to choose a training set. On the other hand, the NN 2 doesn't need the training set, and a knowledge - based system which uses human geographical knowledge improves the Classification results, compared with the conventional statistical method. We propose a pattern classification method that integrates advantages of both the neural networks and the knowledge-based system. The proposed system is divided into three sub-systems which consist of a preprocessing component, a recognition component, and an error correction component. We use the NN2 for choosing the training set as a preprocessor of the NN1, the NN1 for classification, and the knowledge-based system for correcting mis-classification created by the NN1. Experimental results illustrate the performance of the proposed system.","subitem_description_type":"Other"}]},"item_2_description_15":{"attribute_name":"表示順","attribute_value_mlt":[{"subitem_description":"10","subitem_description_type":"Other"}]},"item_2_description_16":{"attribute_name":"アクセション番号","attribute_value_mlt":[{"subitem_description":"KJ00000202942","subitem_description_type":"Other"}]},"item_2_description_8":{"attribute_name":"記事種別(日)","attribute_value_mlt":[{"subitem_description":"地域研究","subitem_description_type":"Other"}]},"item_2_description_9":{"attribute_name":"記事種別(英)","attribute_value_mlt":[{"subitem_description":"BUSSINESS COMMUNITY STUDY","subitem_description_type":"Other"}]},"item_2_source_id_1":{"attribute_name":"雑誌書誌ID","attribute_value_mlt":[{"subitem_source_identifier":"AN10512720","subitem_source_identifier_type":"NCID"}]},"item_2_text_6":{"attribute_name":"著者所属(日)","attribute_value_mlt":[{"subitem_text_value":"四国大学経営情報研究所"}]},"item_2_text_7":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_language":"en","subitem_text_value":"RESEARCH INSTITUTE OF MANAGEMENT AND INFORMATION SCIENCE SHIKOKU UNIVERSITY"}]},"item_2_title_3":{"attribute_name":"論文名よみ","attribute_value_mlt":[{"subitem_title":"リモート センシング ニヨル トクシマシ チュウシンブ ノ トチ リヨウ ジョウキョウ カイセキ"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"村井, 礼"},{"creatorName":"ムライ, ヒロシ","creatorNameLang":"ja-Kana"}],"nameIdentifiers":[{"nameIdentifier":"369","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"Murai, Hiroshi","creatorNameLang":"en"}],"nameIdentifiers":[{"nameIdentifier":"370","nameIdentifierScheme":"WEKO"}]}]},"item_files":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_date","date":[{"dateType":"Available","dateValue":"2016-10-21"}],"displaytype":"detail","filename":"KJ00000202942.pdf","filesize":[{"value":"910.4 kB"}],"format":"application/pdf","licensetype":"license_11","mimetype":"application/pdf","url":{"label":"KJ00000202942.pdf","url":"https://shikoku-u.repo.nii.ac.jp/record/205/files/KJ00000202942.pdf"},"version_id":"f4acd0ad-c4d8-478a-82dd-c9526933bea9"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"Neural Network","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"Remote Sensing","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"Pattern Classification","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"Knowledge-Based Processing","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"Back-Propagation Method","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"Self-Organized Feature Mapping","subitem_subject_language":"en","subitem_subject_scheme":"Other"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourcetype":"journal article","resourceuri":"http://purl.org/coar/resource_type/c_6501"}]},"item_title":"リモートセンシングによる徳島市中心部の土地利用状況解析","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"リモートセンシングによる徳島市中心部の土地利用状況解析"},{"subitem_title":"Land Cover Mapping of Tokushima City by Remote Sensing Analysis","subitem_title_language":"en"}]},"item_type_id":"2","owner":"3","path":["159"],"pubdate":{"attribute_name":"公開日","attribute_value":"2016-10-21"},"publish_date":"2016-10-21","publish_status":"0","recid":"205","relation_version_is_last":true,"title":["リモートセンシングによる徳島市中心部の土地利用状況解析"],"weko_creator_id":"3","weko_shared_id":-1},"updated":"2023-05-15T15:15:32.868736+00:00"}