WEKO3
アイテム
{"_buckets": {"deposit": "65d4c155-6ec9-40d9-86fc-54b21d49b86b"}, "_deposit": {"created_by": 2, "id": "12891", "owners": [2], "pid": {"revision_id": 0, "type": "depid", "value": "12891"}, "status": "published"}, "_oai": {"id": "oai:nagasaki-u.repo.nii.ac.jp:00012891", "sets": ["65"]}, "author_link": ["47226", "47227", "47225"], "item_9_biblio_info_6": {"attribute_name": "書誌情報", "attribute_value_mlt": [{"bibliographicIssueDates": {"bibliographicIssueDate": "2011", "bibliographicIssueDateType": "Issued"}, "bibliographicIssueNumber": "2", "bibliographicPageEnd": "353", "bibliographicPageStart": "344", "bibliographicVolumeNumber": "6469", "bibliographic_titles": [{"bibliographic_title": "Lecture Notes in Computer Science"}]}]}, "item_9_description_4": {"attribute_name": "抄録", "attribute_value_mlt": [{"subitem_description": "We present a supervised multi-label classification method for automatic image annotation. Our method estimates the annotation labels for a test image by accumulating similarities between the test image and labeled training images. The similarities are measured on the basis of sparse representation of the test image by the training images, which avoids similarity votes for irrelevant classes. Besides, our sparse representation-based multi-label classification can estimate a suitable combination of labels even if the combination is unlearned. Experimental results using the PASCAL dataset suggest effectiveness for image annotation compared to the existing SVM-based multi-labeling methods. Nonlinear mapping of the image representation using the kernel trick is also shown to enhance the annotation performance.", "subitem_description_type": "Abstract"}]}, "item_9_description_5": {"attribute_name": "内容記述", "attribute_value_mlt": [{"subitem_description": "International Workshops on Computer Vision, ACCV 2010; Queenstown; 8 November 2010 through 9 November 2010", "subitem_description_type": "Other"}]}, "item_9_description_63": {"attribute_name": "引用", "attribute_value_mlt": [{"subitem_description": "Lecture Notes in Computer Science, 6469(2), pp.344-353; 2011", "subitem_description_type": "Other"}]}, "item_9_publisher_33": {"attribute_name": "出版者", "attribute_value_mlt": [{"subitem_publisher": "Springer Verlag"}]}, "item_9_rights_13": {"attribute_name": "権利", "attribute_value_mlt": [{"subitem_rights": "© 2011 Springer-Verlag Berlin Heidelberg."}, {"subitem_rights": "The original publication is available at www.springerlink.com"}]}, "item_9_source_id_10": {"attribute_name": "書誌レコードID", "attribute_value_mlt": [{"subitem_source_identifier": "AA0071599X", "subitem_source_identifier_type": "NCID"}]}, "item_9_source_id_7": {"attribute_name": "ISSN", "attribute_value_mlt": [{"subitem_source_identifier": "03029743", "subitem_source_identifier_type": "ISSN"}]}, "item_9_version_type_16": {"attribute_name": "著者版フラグ", "attribute_value_mlt": [{"subitem_version_resource": "http://purl.org/coar/version/c_ab4af688f83e57aa", "subitem_version_type": "AM"}]}, "item_creator": {"attribute_name": "著者", "attribute_type": "creator", "attribute_value_mlt": [{"creatorNames": [{"creatorName": "Sakai, Tomoya"}], "nameIdentifiers": [{"nameIdentifier": "47225", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "Itoh, Hayato"}], "nameIdentifiers": [{"nameIdentifier": "47226", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "Imiya, Atsushi"}], "nameIdentifiers": [{"nameIdentifier": "47227", "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": "2020-12-22"}], "displaytype": "detail", "download_preview_message": "", "file_order": 0, "filename": "LNCS6469_344.pdf", "filesize": [{"value": "1.8 MB"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensetype": "license_free", "mimetype": "application/pdf", "size": 1800000.0, "url": {"label": "LNCS6469_344.pdf", "url": "https://nagasaki-u.repo.nii.ac.jp/record/12891/files/LNCS6469_344.pdf"}, "version_id": "3a9f70d9-457d-4c41-8bb0-015270162b34"}]}, "item_language": {"attribute_name": "言語", "attribute_value_mlt": [{"subitem_language": "eng"}]}, "item_resource_type": {"attribute_name": "資源タイプ", "attribute_value_mlt": [{"resourcetype": "conference paper", "resourceuri": "http://purl.org/coar/resource_type/c_5794"}]}, "item_title": "Multi-label classification for image annotation via sparse similarity voting", "item_titles": {"attribute_name": "タイトル", "attribute_value_mlt": [{"subitem_title": "Multi-label classification for image annotation via sparse similarity voting"}]}, "item_type_id": "9", "owner": "2", "path": ["65"], "permalink_uri": "http://hdl.handle.net/10069/27087", "pubdate": {"attribute_name": "公開日", "attribute_value": "2012-01-11"}, "publish_date": "2012-01-11", "publish_status": "0", "recid": "12891", "relation": {}, "relation_version_is_last": true, "title": ["Multi-label classification for image annotation via sparse similarity voting"], "weko_shared_id": 2}
Multi-label classification for image annotation via sparse similarity voting
http://hdl.handle.net/10069/27087
http://hdl.handle.net/10069/270874bbcc560-c3cc-49f8-ae5c-b3869472ae2d
名前 / ファイル | ライセンス | アクション |
---|---|---|
LNCS6469_344.pdf (1.8 MB)
|
|
Item type | 会議発表論文 / Conference Paper(1) | |||||
---|---|---|---|---|---|---|
公開日 | 2012-01-11 | |||||
タイトル | ||||||
タイトル | Multi-label classification for image annotation via sparse similarity voting | |||||
言語 | ||||||
言語 | eng | |||||
資源タイプ | ||||||
資源タイプ識別子 | http://purl.org/coar/resource_type/c_5794 | |||||
資源タイプ | conference paper | |||||
著者 |
Sakai, Tomoya
× Sakai, Tomoya× Itoh, Hayato× Imiya, Atsushi |
|||||
抄録 | ||||||
内容記述タイプ | Abstract | |||||
内容記述 | We present a supervised multi-label classification method for automatic image annotation. Our method estimates the annotation labels for a test image by accumulating similarities between the test image and labeled training images. The similarities are measured on the basis of sparse representation of the test image by the training images, which avoids similarity votes for irrelevant classes. Besides, our sparse representation-based multi-label classification can estimate a suitable combination of labels even if the combination is unlearned. Experimental results using the PASCAL dataset suggest effectiveness for image annotation compared to the existing SVM-based multi-labeling methods. Nonlinear mapping of the image representation using the kernel trick is also shown to enhance the annotation performance. | |||||
内容記述 | ||||||
内容記述タイプ | Other | |||||
内容記述 | International Workshops on Computer Vision, ACCV 2010; Queenstown; 8 November 2010 through 9 November 2010 | |||||
書誌情報 |
Lecture Notes in Computer Science 巻 6469, 号 2, p. 344-353, 発行日 2011 |
|||||
ISSN | ||||||
収録物識別子タイプ | ISSN | |||||
収録物識別子 | 03029743 | |||||
書誌レコードID | ||||||
収録物識別子タイプ | NCID | |||||
収録物識別子 | AA0071599X | |||||
権利 | ||||||
権利情報 | © 2011 Springer-Verlag Berlin Heidelberg. | |||||
権利 | ||||||
権利情報 | The original publication is available at www.springerlink.com | |||||
著者版フラグ | ||||||
出版タイプ | AM | |||||
出版タイプResource | http://purl.org/coar/version/c_ab4af688f83e57aa | |||||
出版者 | ||||||
出版者 | Springer Verlag | |||||
引用 | ||||||
内容記述タイプ | Other | |||||
内容記述 | Lecture Notes in Computer Science, 6469(2), pp.344-353; 2011 |