{"id":"https://openalex.org/W2304414428","doi":null,"title":"Learning from images by integrating different perspectives","display_name":"Learning from images by integrating different perspectives","publication_year":2008,"publication_date":"2008-01-01","ids":{"openalex":"https://openalex.org/W2304414428","mag":"2304414428"},"language":"en","primary_location":{"id":"mag:2304414428","doi":null,"is_oa":false,"landing_page_url":"http://dl.acm.org/citation.cfm?id=1626644","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null},"volume":null,"type":"article","is_traditional":true,"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/A5103351832","display_name":"Sally A. Goldman","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I204465549","display_name":"Washington University in St. Louis","ror":"https://ror.org/01yc7t268","country_code":"US","type":"education","lineage":["https://openalex.org/I204465549"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sally A. Goldman","raw_affiliation_strings":["Washington University in St. Louis,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Washington University in St. Louis,","institution_ids":["https://openalex.org/I204465549"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5112812132","display_name":"Sharath R. Cholleti","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I204465549","display_name":"Washington University in St. Louis","ror":"https://ror.org/01yc7t268","country_code":"US","type":"education","lineage":["https://openalex.org/I204465549"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sharath R. Cholleti","raw_affiliation_strings":["Washington University in St. Louis,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Washington University in St. Louis,","institution_ids":["https://openalex.org/I204465549"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I204465549"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9599999785423279,"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":0.9599999785423279,"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":0.01679999940097332,"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":0.006000000052154064,"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/multiple-instance-learning","display_name":"multiple instance learning","score":0.7879999876022339},{"id":"https://openalex.org/keywords/content-based-image-retrieval","display_name":"content-based image retrieval","score":0.8730000257492065},{"id":"https://openalex.org/keywords/winnow-algorithm","display_name":"Winnow algorithm","score":0.7269999980926514},{"id":"https://openalex.org/keywords/hypothesis-combination","display_name":"hypothesis combination","score":0.5049999952316284},{"id":"https://openalex.org/keywords/multiple-representations","display_name":"multiple representations","score":0.7799999713897705},{"id":"https://openalex.org/keywords/salient-points","display_name":"salient points","score":0.7910000085830688},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"image segmentation","score":0.8730000257492065},{"id":"https://openalex.org/keywords/segmentation-evaluation","display_name":"segmentation evaluation","score":0.7789999842643738},{"id":"https://openalex.org/keywords/meta-learning","display_name":"meta-learning","score":0.8899999856948853},{"id":"https://openalex.org/keywords/adaptive-weighting","display_name":"adaptive weighting","score":0.32100000977516174},{"id":"https://openalex.org/keywords/medical-image-segmentation","display_name":"medical image segmentation","score":0.7480000257492065},{"id":"https://openalex.org/keywords/ground-truth-estimation","display_name":"ground truth estimation","score":0.9179999828338623}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7360503673553467},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.6578540205955505},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.5941882133483887},{"id":"https://openalex.org/C2780719617","wikidata":"https://www.wikidata.org/wiki/Q1030752","display_name":"Salient","level":2,"score":0.5919206738471985},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5653175115585327},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5522763133049011},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5276055335998535},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5256838798522949},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.5005700588226318},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.4934479296207428},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.49152955412864685},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4895983338356018},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.100115567445755},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"mag:2304414428","doi":null,"is_oa":false,"landing_page_url":"http://dl.acm.org/citation.cfm?id=1626644","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":71,"referenced_works":["https://openalex.org/W76086797","https://openalex.org/W79315950","https://openalex.org/W205822829","https://openalex.org/W334023122","https://openalex.org/W1508960934","https://openalex.org/W1520252399","https://openalex.org/W1524926518","https://openalex.org/W1540386283","https://openalex.org/W1542828881","https://openalex.org/W1547172162","https://openalex.org/W1553832277","https://openalex.org/W1554039773","https://openalex.org/W1558633536","https://openalex.org/W1560331282","https://openalex.org/W1570963478","https://openalex.org/W1571248652","https://openalex.org/W1947777220","https://openalex.org/W1966848801","https://openalex.org/W1970800786","https://openalex.org/W1971415609","https://openalex.org/W1973991804","https://openalex.org/W1988790447","https://openalex.org/W1995897489","https://openalex.org/W1999597401","https://openalex.org/W2011103488","https://openalex.org/W2016961357","https://openalex.org/W2019363670","https://openalex.org/W2031979166","https://openalex.org/W2037563221","https://openalex.org/W2040870580","https://openalex.org/W2045551469","https://openalex.org/W2046434485","https://openalex.org/W2049243721","https://openalex.org/W2049633694","https://openalex.org/W2051084846","https://openalex.org/W2065861851","https://openalex.org/W2080928936","https://openalex.org/W2084165935","https://openalex.org/W2085261163","https://openalex.org/W2089948116","https://openalex.org/W2091632190","https://openalex.org/W2091867141","https://openalex.org/W2096891243","https://openalex.org/W2104599248","https://openalex.org/W2107189314","https://openalex.org/W2107290706","https://openalex.org/W2109868644","https://openalex.org/W2110119381","https://openalex.org/W2111498234","https://openalex.org/W2112092250","https://openalex.org/W2113169966","https://openalex.org/W2115593863","https://openalex.org/W2121927366","https://openalex.org/W2124410428","https://openalex.org/W2129113961","https://openalex.org/W2133059825","https://openalex.org/W2136464939","https://openalex.org/W2136595724","https://openalex.org/W2137493099","https://openalex.org/W2140345930","https://openalex.org/W2140480784","https://openalex.org/W2145072179","https://openalex.org/W2148347694","https://openalex.org/W2149706766","https://openalex.org/W2151103935","https://openalex.org/W2153394113","https://openalex.org/W2154318594","https://openalex.org/W2157831837","https://openalex.org/W2163474322","https://openalex.org/W2169684493","https://openalex.org/W2785349534"],"related_works":["https://openalex.org/W2059171383","https://openalex.org/W2408409365","https://openalex.org/W2125517551","https://openalex.org/W2157118832","https://openalex.org/W4300529042","https://openalex.org/W2049243721","https://openalex.org/W7098104724","https://openalex.org/W1990434651","https://openalex.org/W2364089312","https://openalex.org/W2161967063"],"abstract_inverted_index":{"While":[0],"much":[1],"machine":[2,104],"learning":[3,7,17,87,105,140],"research":[4],"focuses":[5],"on":[6],"tasks":[8],"in":[9,73,141,178,229,248],"which":[10],"one":[11],"begins":[12],"from":[13,55,251],"scratch,":[14],"for":[15,139,201],"many":[16],"scenarios":[18],"an":[19,98],"important":[20,114],"component,":[21],"or":[22,40,276],"even":[23],"the":[24,33,68,77,159,175,179,184,190,214,226,232,245,266,280],"entire":[25],"task,":[26],"is":[27,70,119,262],"to":[28,31,111,120,212,218,231,243],"learn":[29],"how":[30],"combine":[32,121,213],"predictions":[34,54],"made":[35],"by":[36,164],"several":[37],"independent":[38],"algorithms":[39],"experts.":[41],"In":[42,144],"this":[43,81,149,260],"dissertation,":[44],"we":[45,59,134,151,182,237,264],"study":[46,60,183],"a":[47,61,74,84,91,102,153,166,170,208,220,239,277],"variety":[48,177],"of":[49,63,76,116,132,148,161,186,189,204,259,279],"problems":[50],"that":[51,95,157,223,263],"involve":[52],"combining":[53],"multiple":[56,125,187,252],"sources.":[57],"\r\nFirst,":[58],"type":[62],"content-based":[64],"image":[65,192],"retrieval":[66],"where":[67],"user":[69],"only":[71],"interested":[72],"portion":[75],"image.":[78,180,235],"We":[79,206],"model":[80],"task":[82],"as":[83,146,169,273],"multiple-instance":[85],"(MI)":[86],"problem":[88,100,106],"and":[89,107],"describe":[90,207],"new":[92,154,209,240],"algorithm,":[93,241],"MI-Winnow,":[94,133],"first":[96],"converts":[97],"MI":[99,142],"into":[101],"regular":[103],"then":[108],"uses":[109],"Winnow":[110],"learn.":[112],"One":[113],"component":[115],"our":[117],"work":[118,261],"hypotheses":[122],"generated":[123],"using":[124,165,193],"representations.":[126],"Along":[127],"with":[128],"providing":[129],"experimental":[130],"evaluation":[131,185],"present":[135,152,238],"some":[136],"theoretical":[137],"results":[138],"setting.":[143],"addition,":[145],"part":[147],"work,":[150],"salient-point":[155],"representation":[156],"reduces":[158],"number":[160],"salient":[162],"points":[163],"segmentation":[167],"algorithm":[168,211],"mask":[171],"but":[172],"still":[173],"preserves":[174],"overall":[176],"\r\nNext,":[181],"segmentations":[188],"same":[191],"different":[194,202],"existing":[195,215],"evaluators":[196,217,228],"each":[197],"being":[198],"best":[199],"suited":[200],"types":[203],"images.":[205],"meta-learning":[210],"base":[216,227],"create":[219],"better":[221],"evaluator":[222],"adaptively":[224],"weights":[225],"response":[230],"specific":[233],"input":[234],"\r\nFinally,":[236],"Veritas,":[242],"estimate":[244],"ground":[246],"truth":[247],"medical":[249],"images":[250,275],"expert":[253,281],"segmentations.":[254,282],"A":[255],"very":[256],"unique":[257],"aspect":[258],"perform":[265],"combination":[267],"without":[268],"any":[269],"training":[270],"data,":[271],"such":[272],"labeled":[274],"ranking":[278]},"counts_by_year":[],"updated_date":"2026-09-26T08:19:03.415552","created_date":"2016-06-24T00:00:00"}