{"id":"https://openalex.org/W2040906419","doi":"https://doi.org/10.1142/s0218001404003198","title":"FROM IMAGE FEATURES TO SYMBOLS AND VICE VERSA \u2014 USING GRAPHS TO LOOP DATA- AND MODEL-DRIVEN PROCESSING IN VISUAL ASSEMBLY RECOGNITION","display_name":"FROM IMAGE FEATURES TO SYMBOLS AND VICE VERSA \u2014 USING GRAPHS TO LOOP DATA- AND MODEL-DRIVEN PROCESSING IN VISUAL ASSEMBLY RECOGNITION","publication_year":2004,"publication_date":"2004-05-01","ids":{"openalex":"https://openalex.org/W2040906419","doi":"https://doi.org/10.1142/s0218001404003198","mag":"2040906419"},"language":"en","primary_location":{"id":"doi:10.1142/s0218001404003198","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218001404003198","pdf_url":null,"source":{"id":"https://openalex.org/S41486457","display_name":"International Journal of Pattern Recognition and Artificial Intelligence","issn_l":"0218-0014","issn":["0218-0014","1793-6381"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Pattern Recognition and Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"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/A5003875445","display_name":"Christian Bauckhage","orcid":"https://orcid.org/0000-0001-6615-2128"},"institutions":[{"id":"https://openalex.org/I20121455","display_name":"Bielefeld University","ror":"https://ror.org/02hpadn98","country_code":"DE","type":"education","lineage":["https://openalex.org/I20121455"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"CHRISTIAN BAUCKHAGE","raw_affiliation_strings":["Applied Computer Science Group, Technical Faculty, Bielefeld University, P.O. Box 100131, 33501 Bielefeld, Germany"],"affiliations":[{"raw_affiliation_string":"Applied Computer Science Group, Technical Faculty, Bielefeld University, P.O. Box 100131, 33501 Bielefeld, Germany","institution_ids":["https://openalex.org/I20121455"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025512646","display_name":"Elke Braun","orcid":null},"institutions":[{"id":"https://openalex.org/I20121455","display_name":"Bielefeld University","ror":"https://ror.org/02hpadn98","country_code":"DE","type":"education","lineage":["https://openalex.org/I20121455"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"ELKE BRAUN","raw_affiliation_strings":["Applied Computer Science Group, Technical Faculty, Bielefeld University, P.O. Box 100131, 33501 Bielefeld, Germany"],"affiliations":[{"raw_affiliation_string":"Applied Computer Science Group, Technical Faculty, Bielefeld University, P.O. Box 100131, 33501 Bielefeld, Germany","institution_ids":["https://openalex.org/I20121455"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079251562","display_name":"Gerhard Sagerer","orcid":null},"institutions":[{"id":"https://openalex.org/I20121455","display_name":"Bielefeld University","ror":"https://ror.org/02hpadn98","country_code":"DE","type":"education","lineage":["https://openalex.org/I20121455"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"GERHARD SAGERER","raw_affiliation_strings":["Applied Computer Science Group, Technical Faculty, Bielefeld University, P.O. Box 100131, 33501 Bielefeld, Germany"],"affiliations":[{"raw_affiliation_string":"Applied Computer Science Group, Technical Faculty, Bielefeld University, P.O. Box 100131, 33501 Bielefeld, Germany","institution_ids":["https://openalex.org/I20121455"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5003875445"],"corresponding_institution_ids":["https://openalex.org/I20121455"],"apc_list":null,"apc_paid":null,"fwci":1.6552,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.84722327,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"18","issue":"03","first_page":"497","last_page":"517"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12292","display_name":"Graph Theory and Algorithms","score":0.9975000023841858,"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/T12292","display_name":"Graph Theory and Algorithms","score":0.9975000023841858,"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/T11159","display_name":"Manufacturing Process and Optimization","score":0.9973000288009644,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10215","display_name":"Semantic Web and Ontologies","score":0.9894000291824341,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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":0.7192380428314209},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5219213962554932},{"id":"https://openalex.org/keywords/cognitive-neuroscience-of-visual-object-recognition","display_name":"Cognitive neuroscience of visual object recognition","score":0.49234116077423096},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.4842931628227234},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.47791868448257446},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4762156903743744},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.4296116530895233},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4101039171218872},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.33327093720436096},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1261833906173706}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7192380428314209},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5219213962554932},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.49234116077423096},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4842931628227234},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.47791868448257446},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4762156903743744},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.4296116530895233},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4101039171218872},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.33327093720436096},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1261833906173706},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"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/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1142/s0218001404003198","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218001404003198","pdf_url":null,"source":{"id":"https://openalex.org/S41486457","display_name":"International Journal of Pattern Recognition and Artificial Intelligence","issn_l":"0218-0014","issn":["0218-0014","1793-6381"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Pattern Recognition and Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:pub.librecat.org:1607699","is_oa":false,"landing_page_url":"https://pub.uni-bielefeld.de/record/1607699","pdf_url":null,"source":{"id":"https://openalex.org/S4306401671","display_name":"PUB \u2013 Publications at Bielefeld University (Bielefeld University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I20121455","host_organization_name":"Bielefeld University","host_organization_lineage":["https://openalex.org/I20121455"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Bauckhage C, Braun E, Sagerer G. From image features to symbols and vice versa - Using graphs to loop data- and model-driven processing in visual assembly recognition. <em>International Journal of Pattern Recognition and Artificial Intelligence</em>. 2004;18(03):497-517.","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.5699999928474426,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1607588461","https://openalex.org/W2013500537","https://openalex.org/W2033001803","https://openalex.org/W2037660182","https://openalex.org/W2083216665","https://openalex.org/W2119171356","https://openalex.org/W2122929441","https://openalex.org/W2151645094","https://openalex.org/W2155748157","https://openalex.org/W2171558287","https://openalex.org/W2171613445","https://openalex.org/W3022352042","https://openalex.org/W4236083764","https://openalex.org/W4302428745"],"related_works":["https://openalex.org/W1972035260","https://openalex.org/W2062195135","https://openalex.org/W1834370135","https://openalex.org/W2114275278","https://openalex.org/W2769899322","https://openalex.org/W1489511283","https://openalex.org/W2974914859","https://openalex.org/W2110244802","https://openalex.org/W949345935","https://openalex.org/W2060811007"],"abstract_inverted_index":{"Graphs":[0,23],"and":[1,12,83,88,91,183,213],"graph":[2,43,93,134,160,206],"matching":[3,44,207],"are":[4,109,120,145,173],"powerful":[5],"mechanisms":[6],"for":[7,76,86],"knowledge":[8,70,170,198],"representation,":[9],"pattern":[10],"recognition":[11,47,87],"machine":[13],"learning.":[14],"Especially":[15],"in":[16,147],"computer":[17],"vision":[18],"their":[19],"application":[20],"is":[21,101,127,130],"manifold.":[22],"can":[24,45,154],"characterize":[25],"relations":[26,179],"among":[27],"image":[28,113,181],"features":[29,182],"like":[30,143],"points":[31],"or":[32],"regions":[33],"but":[34],"they":[35,172],"may":[36,61,201],"also":[37,62],"represent":[38,178],"symbolic":[39,141],"object":[40],"knowledge.":[41],"Hence,":[42],"accomplish":[46],"tasks":[48],"on":[49,208],"different":[50,67],"levels":[51,68],"of":[52,69,117,159,189],"abstraction.":[53],"In":[54],"this":[55,144],"contribution,":[56],"we":[57],"demonstrate":[58],"that":[59,80,135,151],"graphs":[60,167,176],"bridge":[63],"the":[64,138,163,186,190],"gap":[65],"between":[66,180],"representation.":[71],"We":[72],"present":[73],"a":[74,133,148,209],"system":[75],"visual":[77,187],"assembly":[78,125],"monitoring":[79],"integrates":[81],"bottom-up":[82,215],"top-down":[84,169],"strategies":[85],"automatically":[89],"generates":[90],"learns":[92],"models":[94,137,142],"to":[95,196],"recognize":[96],"assembled":[97],"objects.":[98],"Data-driven":[99],"processing":[100,216],"subdived":[102],"into":[103,132,175],"three":[104],"stages:":[105],"first,":[106],"elementary":[107,118],"objects":[108,119],"recognized":[110,156,204],"from":[111,205],"low-level":[112],"features.":[114],"Then,":[115],"clusters":[116],"analyzed":[121],"syntactically;":[122],"if":[123],"an":[124],"structure":[126],"found,":[128],"it":[129],"translated":[131],"uniquely":[136],"assembly.":[139,193],"Finally,":[140],"stored":[146],"database":[149],"so":[150],"individual":[152],"assemblies":[153,200],"be":[155,203],"by":[157],"means":[158],"matching.":[161],"At":[162],"same":[164],"time,":[165],"these":[166],"enable":[168],"propagation:":[171],"transformed":[174],"which":[177],"thus":[184],"describe":[185],"appearance":[188],"recently":[191],"found":[192],"Therefore,":[194],"due":[195],"model-driven":[197],"propagation":[199],"subsequently":[202],"lower":[210],"computational":[211],"level":[212],"tedious":[214],"becomes":[217],"superfluous.":[218]},"counts_by_year":[],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}