{"id":"https://openalex.org/W3010411489","doi":"https://doi.org/10.1145/3374587.3374645","title":"An Attention-based Sequence Learning Model for Scene Text Recognition with Text Correction","display_name":"An Attention-based Sequence Learning Model for Scene Text Recognition with Text Correction","publication_year":2019,"publication_date":"2019-12-06","ids":{"openalex":"https://openalex.org/W3010411489","doi":"https://doi.org/10.1145/3374587.3374645","mag":"3010411489"},"language":"en","primary_location":{"id":"doi:10.1145/3374587.3374645","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3374587.3374645","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 3rd International Conference on Computer Science and Artificial Intelligence","raw_type":"proceedings-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/A5100630016","display_name":"Chen Fang","orcid":"https://orcid.org/0000-0002-6601-4267"},"institutions":[{"id":"https://openalex.org/I142108993","display_name":"Southwest University","ror":"https://ror.org/01kj4z117","country_code":"CN","type":"education","lineage":["https://openalex.org/I142108993"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Fang Chen","raw_affiliation_strings":["Southwest University, Chongqing, China"],"affiliations":[{"raw_affiliation_string":"Southwest University, Chongqing, China","institution_ids":["https://openalex.org/I142108993"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047341940","display_name":"Guoqiang Xiao","orcid":"https://orcid.org/0000-0003-2165-476X"},"institutions":[{"id":"https://openalex.org/I142108993","display_name":"Southwest University","ror":"https://ror.org/01kj4z117","country_code":"CN","type":"education","lineage":["https://openalex.org/I142108993"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guoqiang Xiao","raw_affiliation_strings":["Southwest University, Chongqing, China"],"affiliations":[{"raw_affiliation_string":"Southwest University, Chongqing, China","institution_ids":["https://openalex.org/I142108993"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5104386041","display_name":"Conghui Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I142108993","display_name":"Southwest University","ror":"https://ror.org/01kj4z117","country_code":"CN","type":"education","lineage":["https://openalex.org/I142108993"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Conghui Chen","raw_affiliation_strings":["Southwest University, Chongqing, China"],"affiliations":[{"raw_affiliation_string":"Southwest University, Chongqing, China","institution_ids":["https://openalex.org/I142108993"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100630016"],"corresponding_institution_ids":["https://openalex.org/I142108993"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.18794326,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"90","issue":null,"first_page":"215","last_page":"220"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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/T14339","display_name":"Image Processing and 3D Reconstruction","score":0.996999979019165,"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":0.9890000224113464,"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":0.7513165473937988},{"id":"https://openalex.org/keywords/text-recognition","display_name":"Text recognition","score":0.6366825103759766},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.6127756834030151},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.607616126537323},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5499101877212524},{"id":"https://openalex.org/keywords/sequence-learning","display_name":"Sequence learning","score":0.4689459502696991},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.41332292556762695},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3745073974132538},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.1775752305984497}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7513165473937988},{"id":"https://openalex.org/C2983812711","wikidata":"https://www.wikidata.org/wiki/Q167555","display_name":"Text recognition","level":3,"score":0.6366825103759766},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.6127756834030151},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.607616126537323},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5499101877212524},{"id":"https://openalex.org/C40506919","wikidata":"https://www.wikidata.org/wiki/Q7452469","display_name":"Sequence learning","level":2,"score":0.4689459502696991},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.41332292556762695},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3745073974132538},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1775752305984497},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3374587.3374645","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3374587.3374645","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 3rd International Conference on Computer Science and Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.7200000286102295}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W6908809","https://openalex.org/W603908379","https://openalex.org/W654550266","https://openalex.org/W1491389626","https://openalex.org/W1971822075","https://openalex.org/W1998042868","https://openalex.org/W2008806374","https://openalex.org/W2049951199","https://openalex.org/W2099247484","https://openalex.org/W2128409098","https://openalex.org/W2130942839","https://openalex.org/W2133564696","https://openalex.org/W2144554289","https://openalex.org/W2146835493","https://openalex.org/W2163605009","https://openalex.org/W2194187530","https://openalex.org/W2343052201","https://openalex.org/W2520774990","https://openalex.org/W2750938222","https://openalex.org/W2795619303","https://openalex.org/W2810983211","https://openalex.org/W2963480192","https://openalex.org/W2963526661","https://openalex.org/W3106271744","https://openalex.org/W6600284362","https://openalex.org/W6618372016","https://openalex.org/W6649973027","https://openalex.org/W6652761251"],"related_works":["https://openalex.org/W2112284452","https://openalex.org/W2146514770","https://openalex.org/W3085798047","https://openalex.org/W2374269412","https://openalex.org/W371123309","https://openalex.org/W2085500676","https://openalex.org/W2883195674","https://openalex.org/W2072736607","https://openalex.org/W3080374445","https://openalex.org/W2964790801"],"abstract_inverted_index":{"Recognizing":[0],"text":[1,56,61,72,77,88],"from":[2],"images":[3,29,119],"taken":[4],"in":[5,17,27],"natural":[6,28],"scenes":[7],"is":[8,65,91,180],"a":[9,13,50,55,60,83,92,145],"challenging":[10],"task":[11],"and":[12,59,107,120,166],"hot":[14],"research":[15],"topic":[16],"computer":[18],"vision.":[19],"Unlike":[20],"traditional":[21],"optical":[22],"character":[23],"recognition":[24,57,89],"(OCR),":[25],"words":[26],"often":[30],"possess":[31],"irregular":[32,69],"layout":[33],"(e.g.":[34],"arbitrarily":[35],"orientation,":[36],"blurring,":[37],"perspective":[38],"distortion)":[39],"which":[40,64],"are":[41,114],"difficult":[42],"to":[43,68,82,155,159,182],"recognize.":[44],"In":[45],"this":[46],"paper,":[47],"we":[48,143],"develop":[49],"novel":[51],"method":[52,179],"consisting":[53],"of":[54,78],"network":[58,90],"correction":[62,73],"component,":[63],"more":[66,84,93,161],"robust":[67],"text.":[70,86,110],"The":[71,87,111,123],"component":[74],"rectify":[75],"the":[76,102,109,130,138,151,157,177],"an":[79],"input":[80,106],"image":[81,104],"\"readable\"":[85],"\"location":[94],"aware\"":[95],"attention-based":[96],"sequence":[97],"learning":[98],"model":[99,158],"that":[100],"take":[101],"rectified":[103],"as":[105],"recognize":[108],"entire":[112],"networks":[113],"trained":[115],"jointly":[116],"by":[117],"only":[118,128],"word-level":[121],"annotations.":[122],"standard":[124,174],"Softmax":[125,152],"loss":[126,147,153],"function":[127,148,154],"considers":[129],"separability":[131],"between":[132],"classes":[133],"but":[134],"does":[135],"not":[136],"restrict":[137],"aggregation":[139],"within":[140],"classes.":[141],"Therefore,":[142],"adopt":[144],"new":[146],"based":[149],"on":[150,171],"enable":[156],"learn":[160],"discriminative":[162],"features,":[163],"reduce":[164],"misjudgments":[165],"improve":[167],"accuracy.":[168],"Extensive":[169],"experiments":[170],"seven":[172],"popular":[173],"benchmarks,":[175],"demonstrate":[176],"proposed":[178],"comparable":[181],"state-of-the-art":[183],"performance.":[184]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
