{"created":"2025-01-19T00:08:34.077465+00:00","updated":"2025-01-21T00:34:52.659223+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00129345","sets":["6504:8103:8109"]},"path":["8109"],"owner":"1","recid":"129345","title":["RS画像データのMLHとNN分類結果の比較評価"],"pubdate":{"attribute_name":"公開日","attribute_value":"1996-03-06"},"_buckets":{"deposit":"582e44fe-b6a2-45ec-87a2-6ebadbb3f037"},"_deposit":{"id":"129345","pid":{"type":"depid","value":"129345","revision_id":0},"owners":[1],"status":"published","created_by":1},"item_title":"RS画像データのMLHとNN分類結果の比較評価","author_link":[],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"RS画像データのMLHとNN分類結果の比較評価"},{"subitem_title":"Evaluation conparison of RS image data classification results using NN and MLH.","subitem_title_language":"en"}]},"item_type_id":"22","publish_date":"1996-03-06","item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_22_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"茨城大学 工学部"},{"subitem_text_value":"茨城大学 工学部"},{"subitem_text_value":"茨城大学 工学部"}]},"item_22_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Faculty of engineering,Ibaraki University","subitem_text_language":"en"},{"subitem_text_value":"Faculty of engineering,Ibaraki University","subitem_text_language":"en"},{"subitem_text_value":"Faculty of engineering,Ibaraki University","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/129345/files/KJ00001329556.pdf"},"date":[{"dateType":"Available","dateValue":"1996-03-06"}],"format":"application/pdf","filename":"KJ00001329556.pdf","filesize":[{"value":"251.1 kB"}],"mimetype":"application/pdf","accessrole":"open_date","version_id":"d7663905-707d-40e2-b0c8-9e4fbb59ed52","displaytype":"detail","licensetype":"license_note"}]},"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_22_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN00349328","subitem_source_identifier_type":"NCID"}]},"item_22_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"現在リモートセンシング画像データの分類法としては最大尤度法(MLH)が最も多く用いられてきている。これは、MLHが画素データの分布に合わせて尤度関数を定義し分類するものであり、統計的取り扱いが容易であるためであろう。本研究では、最近研究が行われてきているニューラルネットワーク(NN)分類法をアルゴリズム化したので両者の分類法をリモートセンシング画像データに適用し、分類法による分類結果の相違をパターンの種類や境界部分でアクティブィティー尺度を用いることによって比較評価する。","subitem_description_type":"Other"}]},"item_22_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"228","bibliographic_titles":[{"bibliographic_title":"全国大会講演論文集"}],"bibliographicPageStart":"227","bibliographicIssueDates":{"bibliographicIssueDate":"1996-03-06","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"メディア情報処理","bibliographicVolumeNumber":"第52回"}]},"relation_version_is_last":true,"weko_creator_id":"1"},"id":129345,"links":{}}