{"id":"https://openalex.org/W23955754","doi":"https://doi.org/10.1109/tip.2013.2277818","title":"031 \u7523\u8925\u65e9\u671f\u306e\u4e0b\u80a2\u6d6e\u816b\u306b\u95a2\u3059\u308b\u7814\u7a76 : \u7b2c2\u5831: \u5e1d\u738b\u5207\u958b\u8853\u5f8c\u306e\u7523\u8925\u306e\u4e0b\u80a2\u6d6e\u816b\u306b\u5bfe\u3059\u308b\u5f3e\u6027\u30b9\u30c8\u30c3\u30ad\u30f3\u30b0\u306e\u52b9\u679c(\u598a\u5a20\u3001\u5206\u5a29\u3001\u7523\u89256, \u7b2c46\u56de \u65e5\u672c\u6bcd\u6027\u885b\u751f\u5b66\u4f1a\u7dcf\u4f1a \u5b66\u8853\u96c6\u4f1a\u6284\u9332\u96c6)","display_name":"031 \u7523\u8925\u65e9\u671f\u306e\u4e0b\u80a2\u6d6e\u816b\u306b\u95a2\u3059\u308b\u7814\u7a76 : \u7b2c2\u5831: \u5e1d\u738b\u5207\u958b\u8853\u5f8c\u306e\u7523\u8925\u306e\u4e0b\u80a2\u6d6e\u816b\u306b\u5bfe\u3059\u308b\u5f3e\u6027\u30b9\u30c8\u30c3\u30ad\u30f3\u30b0\u306e\u52b9\u679c(\u598a\u5a20\u3001\u5206\u5a29\u3001\u7523\u89256, \u7b2c46\u56de \u65e5\u672c\u6bcd\u6027\u885b\u751f\u5b66\u4f1a\u7dcf\u4f1a \u5b66\u8853\u96c6\u4f1a\u6284\u9332\u96c6)","publication_year":2005,"publication_date":"2005-09-01","ids":{"openalex":"https://openalex.org/W23955754","doi":"https://doi.org/10.1109/tip.2013.2277818","mag":"23955754"},"language":"en","primary_location":{"id":"mag:23955754","is_oa":false,"landing_page_url":"http://ci.nii.ac.jp/naid/110003493408/","pdf_url":null,"source":{"id":"https://openalex.org/S4306553049","display_name":"\u6bcd\u6027\u885b\u751f","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"\u6bcd\u6027\u885b\u751f","raw_type":null},"type":"article","indexed_in":[],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5004972227","display_name":"\u771f\u7531\u7f8e \u5b89\u90e8","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"\u771f\u7531\u7f8e \u5b89\u90e8","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053956670","display_name":"\u7f8e\u548c \u798f\u6e80","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"\u7f8e\u548c \u798f\u6e80","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5020961417","display_name":"\u6566\u5b50 \u4e45\u4fdd","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"\u6566\u5b50 \u4e45\u4fdd","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.00254085,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"46","issue":"3","first_page":"113","last_page":"23"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.7982000112533569,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.7982000112533569,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.061500001698732376,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.05999999865889549,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.33263975381851196}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.33263975381851196}],"mesh":[],"locations_count":1,"locations":[{"id":"mag:23955754","is_oa":false,"landing_page_url":"http://ci.nii.ac.jp/naid/110003493408/","pdf_url":null,"source":{"id":"https://openalex.org/S4306553049","display_name":"\u6bcd\u6027\u885b\u751f","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"\u6bcd\u6027\u885b\u751f","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"This":[0,19],"paper":[1,135],"presents":[2],"a":[3,12,52,60,109,142],"new":[4,13],"automatic":[5],"image":[6,37,42,56,84],"annotation":[7,57,85,102,154],"algorithm.":[8],"First,":[9],"we":[10],"introduce":[11],"similarity":[14,28,143],"measure":[15,47,144],"between":[16,29],"images:":[17],"compactness.":[18],"uses":[20],"low":[21,148],"level":[22,149],"visual":[23],"descriptors":[24],"for":[25,51,62],"determining":[26],"the":[27,49,93,96,137],"two":[30],"images.":[31],"Compactness":[32],"shows":[33],"how":[34],"close":[35],"test":[36],"features":[38],"lie":[39],"to":[40],"training":[41,111],"feature":[43,116,150],"cluster":[44],"centers.":[45],"The":[46,76,87,104,130],"provides":[48],"core":[50],"k-nearest":[53],"neighbor":[54],"type":[55],"method.":[58],"Afterward,":[59],"formalism":[61],"defining":[63],"different":[64,115],"transfer":[65,72],"techniques":[66,73],"is":[67,80],"devised":[68],"and":[69,118,152],"several":[70],"label":[71,158],"are":[74,136],"provided.":[75],"method":[77,105],"as":[78,141],"whole":[79],"evaluated":[81],"on":[82,89,157],"four":[83],"benchmarks.":[86],"results":[88],"these":[90],"sets":[91],"validate":[92],"accuracy":[94],"of":[95,133,139],"approach,":[97],"which":[98],"outperforms":[99],"many":[100],"state-of-the-art":[101],"methods.":[103],"presented":[106],"here":[107],"requires":[108],"simple":[110],"process,":[112],"efficiently":[113],"combines":[114],"types":[117],"performs":[119],"better":[120],"than":[121],"complex":[122],"learning":[123],"algorithms,":[124],"even":[125],"in":[126],"this":[127,134],"incipient":[128],"form.":[129],"main":[131],"contributions":[132],"usage":[138],"compactness":[140],"that":[145],"enables":[146],"efficient":[147],"comparison":[151],"an":[153],"algorithm":[155],"based":[156],"transfer.":[159]},"counts_by_year":[],"updated_date":"2025-07-23T07:10:33.562985","created_date":"2016-06-24T00:00:00"}