{"id":"https://openalex.org/W3160289536","doi":"https://doi.org/10.1109/icpr48806.2021.9412671","title":"Robust Lexicon-Free Confidence Prediction for Text Recognition","display_name":"Robust Lexicon-Free Confidence Prediction for Text Recognition","publication_year":2021,"publication_date":"2021-01-10","ids":{"openalex":"https://openalex.org/W3160289536","doi":"https://doi.org/10.1109/icpr48806.2021.9412671","mag":"3160289536"},"language":"en","primary_location":{"id":"doi:10.1109/icpr48806.2021.9412671","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr48806.2021.9412671","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 25th International Conference on Pattern Recognition (ICPR)","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/A5100748969","display_name":"Qi Song","orcid":"https://orcid.org/0000-0002-1726-7858"},"institutions":[{"id":"https://openalex.org/I4210087373","display_name":"Meizu (China)","ror":"https://ror.org/0067g4302","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210087373"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qi Song","raw_affiliation_strings":["Meituan, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Meituan, Beijing, China","institution_ids":["https://openalex.org/I4210087373"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073437730","display_name":"Qianyi Jiang","orcid":"https://orcid.org/0000-0002-6006-9929"},"institutions":[{"id":"https://openalex.org/I4210087373","display_name":"Meizu (China)","ror":"https://ror.org/0067g4302","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210087373"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qianyi Jiang","raw_affiliation_strings":["Meituan, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Meituan, Beijing, China","institution_ids":["https://openalex.org/I4210087373"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100421978","display_name":"Rui Zhang","orcid":"https://orcid.org/0000-0001-9418-0863"},"institutions":[{"id":"https://openalex.org/I4210087373","display_name":"Meizu (China)","ror":"https://ror.org/0067g4302","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210087373"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rui Zhang","raw_affiliation_strings":["Meituan, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Meituan, Beijing, China","institution_ids":["https://openalex.org/I4210087373"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009222019","display_name":"Xiaolin Wei","orcid":"https://orcid.org/0000-0002-3983-047X"},"institutions":[{"id":"https://openalex.org/I4210087373","display_name":"Meizu (China)","ror":"https://ror.org/0067g4302","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210087373"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaolin Wei","raw_affiliation_strings":["Meituan, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Meituan, Beijing, China","institution_ids":["https://openalex.org/I4210087373"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210087373"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"abs 1904 1375","issue":null,"first_page":"3232","last_page":"3239"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10601","display_name":"Handwritten Text Recognition Techniques","score":1.0,"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/T10601","display_name":"Handwritten Text Recognition Techniques","score":1.0,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9929999709129333,"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/T11309","display_name":"Music and Audio Processing","score":0.989799976348877,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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":0.8157912492752075},{"id":"https://openalex.org/keywords/voting","display_name":"Voting","score":0.7405791282653809},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6001821756362915},{"id":"https://openalex.org/keywords/lexicon","display_name":"Lexicon","score":0.5883764624595642},{"id":"https://openalex.org/keywords/optical-character-recognition","display_name":"Optical character recognition","score":0.534204363822937},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.44875746965408325},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.44345566630363464},{"id":"https://openalex.org/keywords/majority-rule","display_name":"Majority rule","score":0.4366905391216278},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.37045425176620483},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.33006030321121216}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8157912492752075},{"id":"https://openalex.org/C520049643","wikidata":"https://www.wikidata.org/wiki/Q189760","display_name":"Voting","level":3,"score":0.7405791282653809},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6001821756362915},{"id":"https://openalex.org/C2778121359","wikidata":"https://www.wikidata.org/wiki/Q8096","display_name":"Lexicon","level":2,"score":0.5883764624595642},{"id":"https://openalex.org/C546480517","wikidata":"https://www.wikidata.org/wiki/Q167555","display_name":"Optical character recognition","level":3,"score":0.534204363822937},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.44875746965408325},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.44345566630363464},{"id":"https://openalex.org/C153668964","wikidata":"https://www.wikidata.org/wiki/Q27636","display_name":"Majority rule","level":2,"score":0.4366905391216278},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.37045425176620483},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33006030321121216},{"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/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"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":1,"locations":[{"id":"doi:10.1109/icpr48806.2021.9412671","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr48806.2021.9412671","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 25th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.6100000143051147}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W1491389626","https://openalex.org/W1521064364","https://openalex.org/W1972065312","https://openalex.org/W1978729128","https://openalex.org/W1998042868","https://openalex.org/W2008806374","https://openalex.org/W2034537249","https://openalex.org/W2061802763","https://openalex.org/W2127141656","https://openalex.org/W2157399234","https://openalex.org/W2194187530","https://openalex.org/W2294053032","https://openalex.org/W2402144811","https://openalex.org/W2593572697","https://openalex.org/W2623860192","https://openalex.org/W2754613063","https://openalex.org/W2802270051","https://openalex.org/W2810983211","https://openalex.org/W2884585870","https://openalex.org/W2928555987","https://openalex.org/W2953384591","https://openalex.org/W2963263347","https://openalex.org/W2963360699","https://openalex.org/W2963403868","https://openalex.org/W2963648432","https://openalex.org/W2964065044","https://openalex.org/W2978036638","https://openalex.org/W2997864923","https://openalex.org/W3013224334","https://openalex.org/W3014877467","https://openalex.org/W3105789975","https://openalex.org/W3160573439","https://openalex.org/W4385245566","https://openalex.org/W6629590909","https://openalex.org/W6631165897","https://openalex.org/W6642972425","https://openalex.org/W6649973027","https://openalex.org/W6713134421","https://openalex.org/W6734085379","https://openalex.org/W6739901393","https://openalex.org/W6744133147","https://openalex.org/W6746477880","https://openalex.org/W6753412334","https://openalex.org/W6775281705"],"related_works":["https://openalex.org/W2140536630","https://openalex.org/W3195005284","https://openalex.org/W2391730868","https://openalex.org/W3121841074","https://openalex.org/W2901018557","https://openalex.org/W2055572829","https://openalex.org/W1894159578","https://openalex.org/W2807400035","https://openalex.org/W4297796115","https://openalex.org/W3125086856"],"abstract_inverted_index":{"Benefiting":[0],"from":[1],"the":[2,20,39,107,111,115,131,136],"success":[3],"of":[4,74,114,135],"deep":[5],"learning,":[6],"Optical":[7],"Character":[8],"Recognition":[9],"(OCR)":[10],"is":[11,42,123],"booming":[12],"in":[13,29,64,144],"recent":[14],"years.":[15],"As":[16],"we":[17,47],"all":[18],"know,":[19],"text":[21,57,66],"recognition":[22,58,118],"results":[23,40],"are":[24,41],"vulnerable":[25],"to":[26],"slight":[27],"perturbation":[28],"input":[30],"images,":[31],"thus":[32],"a":[33,49,56,78,92,101],"method":[34,51,72],"for":[35,52,87],"measuring":[36],"how":[37],"reliable":[38],"crucial.":[43],"In":[44],"this":[45],"paper,":[46],"present":[48],"novel":[50],"confidence":[53,103],"measurement":[54],"given":[55],"result,":[59],"which":[60,129],"can":[61,141],"be":[62,142],"embedded":[63],"any":[65],"recognizer":[67],"with":[68,77],"little":[69],"overheads.":[70],"Our":[71],"consists":[73],"two":[75],"stages":[76],"coarse-to-fine":[79],"style.":[80],"The":[81,97],"first":[82],"stage":[83,99],"generates":[84],"multiple":[85],"candidates":[86],"voting":[88,108],"coarse":[89],"scores":[90],"by":[91,106],"Single-Input":[93],"Multi-Output":[94],"network":[95],"(SIMO).":[96],"second":[98],"calculates":[100],"refined":[102],"score":[104],"referred":[105],"result":[109],"and":[110,133,147],"conditional":[112],"probabilities":[113],"Top-1":[116],"probable":[117],"sequence.":[119],"Highly":[120],"competitive":[121],"performance":[122],"achieved":[124],"on":[125],"several":[126],"standard":[127],"benchmarks":[128],"validate":[130],"efficiency":[132],"effectiveness":[134],"proposed":[137],"method.":[138],"Moreover,":[139],"it":[140],"adopted":[143],"both":[145],"Latin":[146],"non-Latin":[148],"languages.":[149]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}