{"id":"https://openalex.org/W1969239156","doi":"https://doi.org/10.1109/das.2014.59","title":"Business Forms Classification Using Earth Mover's Distance","display_name":"Business Forms Classification Using Earth Mover's Distance","publication_year":2014,"publication_date":"2014-04-01","ids":{"openalex":"https://openalex.org/W1969239156","doi":"https://doi.org/10.1109/das.2014.59","mag":"1969239156"},"language":"en","primary_location":{"id":"doi:10.1109/das.2014.59","is_oa":false,"landing_page_url":"https://doi.org/10.1109/das.2014.59","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 11th IAPR International Workshop on Document Analysis Systems","raw_type":"proceedings-article"},"type":"conference-paper","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/A5112334801","display_name":"Syed Saqib Bukhari","orcid":null},"institutions":[{"id":"https://openalex.org/I153267046","display_name":"University of Kaiserslautern","ror":"https://ror.org/04zrf7b53","country_code":"DE","type":"education","lineage":["https://openalex.org/I153267046"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Syed Saqib Bukhari","raw_affiliation_strings":["University of Kaiserslautern, Kaiserslautern, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Kaiserslautern, Kaiserslautern, Germany","institution_ids":["https://openalex.org/I153267046"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071243852","display_name":"Markus Ebbecke","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Markus Ebbecke","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5010653902","display_name":"Michael Gillmann","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Michael Gillmann","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.5394,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.65924461,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"2","issue":null,"first_page":"11","last_page":"15"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9997000098228455,"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":0.9997000098228455,"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/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.9984999895095825,"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":0.9962999820709229,"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/earth-movers-distance","display_name":"Earth mover's distance","score":0.8888022899627686},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6553982496261597},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5151942372322083},{"id":"https://openalex.org/keywords/work","display_name":"Work (physics)","score":0.46306082606315613},{"id":"https://openalex.org/keywords/first-mover-advantage","display_name":"First-mover advantage","score":0.43266820907592773},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3604785203933716},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3249751329421997},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.19819384813308716},{"id":"https://openalex.org/keywords/mechanical-engineering","display_name":"Mechanical engineering","score":0.09333804249763489},{"id":"https://openalex.org/keywords/management","display_name":"Management","score":0.07458412647247314}],"concepts":[{"id":"https://openalex.org/C82668687","wikidata":"https://www.wikidata.org/wiki/Q3046456","display_name":"Earth mover's distance","level":2,"score":0.8888022899627686},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6553982496261597},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5151942372322083},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.46306082606315613},{"id":"https://openalex.org/C196276664","wikidata":"https://www.wikidata.org/wiki/Q121716","display_name":"First-mover advantage","level":2,"score":0.43266820907592773},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3604785203933716},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3249751329421997},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.19819384813308716},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.09333804249763489},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.07458412647247314},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/das.2014.59","is_oa":false,"landing_page_url":"https://doi.org/10.1109/das.2014.59","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 11th IAPR International Workshop on Document Analysis Systems","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.550000011920929,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321114","display_name":"Bundesministerium f\u00fcr Bildung und Forschung","ror":"https://ror.org/04pz7b180"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1532887042","https://openalex.org/W1533362330","https://openalex.org/W1620186711","https://openalex.org/W2033585316","https://openalex.org/W2053619597","https://openalex.org/W2094710754","https://openalex.org/W2109422812","https://openalex.org/W2139717968","https://openalex.org/W2142995284","https://openalex.org/W2143668817","https://openalex.org/W2170288539","https://openalex.org/W6631659683"],"related_works":["https://openalex.org/W2113049000","https://openalex.org/W2125221595","https://openalex.org/W2396732591","https://openalex.org/W3124321732","https://openalex.org/W1540114044","https://openalex.org/W1536203315","https://openalex.org/W201712113","https://openalex.org/W2015573458","https://openalex.org/W2069209154","https://openalex.org/W1547647895"],"abstract_inverted_index":{"Form":[0],"Classification":[1],"has":[2],"not":[3,22],"been":[4],"focused":[5],"on":[6,98],"for":[7],"the":[8,12,17,24,85,88,109],"last":[9],"decade.":[10],"Unfortunately":[11],"algorithms":[13],"published":[14],"mainly":[15],"in":[16,26],"80s":[18],"and":[19,39,49,79],"90s":[20],"do":[21],"meet":[23],"requirements":[25,40],"our":[27],"present":[28],"commercial":[29],"document":[30],"analysis":[31],"projects.":[32],"There":[33],"we":[34,59],"are":[35],"confronted":[36],"with":[37],"conditions":[38],"unanticipated":[41],"by":[42],"that":[43,73],"research,":[44],"such":[45],"as":[46],"fax":[47,77],"distortions":[48,78],"-":[50,53],"even":[51],"worse":[52],"form":[54,65],"variations.":[55,81],"In":[56],"this":[57],"work":[58],"introduce":[60],"a":[61,99],"new":[62],"color-coded":[63],"pixel-based":[64],"classification":[66,96],"method":[67],"using":[68],"Earth":[69],"Mover's":[70],"Distance":[71],"(EMD)":[72],"is":[74,105],"robust":[75],"against":[76],"content":[80],"Experimental":[82],"results":[83],"prove":[84],"effectiveness":[86],"of":[87],"presented":[89],"method.":[90],"It":[91],"achieved":[92],"more":[93],"than":[94,108],"90%":[95],"accuracy":[97],"real-world":[100],"business":[101],"forms":[102],"dataset,":[103],"which":[104],"significantly":[106],"better":[107],"competing":[110],"state-of-the-art":[111],"methods.":[112]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2015,"cited_by_count":3}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}