{"id":"https://openalex.org/W3109202259","doi":"https://doi.org/10.1109/icpr48806.2021.9412222","title":"On-Device Text Image Super Resolution","display_name":"On-Device Text Image Super Resolution","publication_year":2021,"publication_date":"2021-01-10","ids":{"openalex":"https://openalex.org/W3109202259","doi":"https://doi.org/10.1109/icpr48806.2021.9412222","mag":"3109202259"},"language":"en","primary_location":{"id":"doi:10.1109/icpr48806.2021.9412222","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr48806.2021.9412222","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":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2011.10251","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5109481571","display_name":"Dhruval Jain","orcid":null},"institutions":[{"id":"https://openalex.org/I4210101778","display_name":"Samsung (United States)","ror":"https://ror.org/01bfbvm65","country_code":"US","type":"company","lineage":["https://openalex.org/I2250650973","https://openalex.org/I4210101778"]},{"id":"https://openalex.org/I4210139030","display_name":"Samsung (India)","ror":"https://ror.org/04cpx2569","country_code":"IN","type":"company","lineage":["https://openalex.org/I2250650973","https://openalex.org/I4210139030"]}],"countries":["IN","US"],"is_corresponding":false,"raw_author_name":"Dhruval Jain","raw_affiliation_strings":["OnDevice AI, Samsung R& D Institute, Bangalore, India","[Samsung]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"OnDevice AI, Samsung R& D Institute, Bangalore, India","institution_ids":["https://openalex.org/I4210139030"]},{"raw_affiliation_string":"[Samsung]","institution_ids":["https://openalex.org/I4210101778"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025953920","display_name":"Arun D Prabhu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210101778","display_name":"Samsung (United States)","ror":"https://ror.org/01bfbvm65","country_code":"US","type":"company","lineage":["https://openalex.org/I2250650973","https://openalex.org/I4210101778"]},{"id":"https://openalex.org/I4210139030","display_name":"Samsung (India)","ror":"https://ror.org/04cpx2569","country_code":"IN","type":"company","lineage":["https://openalex.org/I2250650973","https://openalex.org/I4210139030"]}],"countries":["IN","US"],"is_corresponding":false,"raw_author_name":"Arun D Prabhu","raw_affiliation_strings":["OnDevice AI, Samsung R& D Institute, Bangalore, India","[Samsung]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"OnDevice AI, Samsung R& D Institute, Bangalore, India","institution_ids":["https://openalex.org/I4210139030"]},{"raw_affiliation_string":"[Samsung]","institution_ids":["https://openalex.org/I4210101778"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067079195","display_name":"Gopi Ramena","orcid":"https://orcid.org/0000-0002-7498-3973"},"institutions":[{"id":"https://openalex.org/I4210101778","display_name":"Samsung (United States)","ror":"https://ror.org/01bfbvm65","country_code":"US","type":"company","lineage":["https://openalex.org/I2250650973","https://openalex.org/I4210101778"]},{"id":"https://openalex.org/I4210139030","display_name":"Samsung (India)","ror":"https://ror.org/04cpx2569","country_code":"IN","type":"company","lineage":["https://openalex.org/I2250650973","https://openalex.org/I4210139030"]}],"countries":["IN","US"],"is_corresponding":false,"raw_author_name":"Gopi Ramena","raw_affiliation_strings":["OnDevice AI, Samsung R& D Institute, Bangalore, India","[Samsung]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"OnDevice AI, Samsung R& D Institute, Bangalore, India","institution_ids":["https://openalex.org/I4210139030"]},{"raw_affiliation_string":"[Samsung]","institution_ids":["https://openalex.org/I4210101778"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Manoi Goyal","orcid":null},"institutions":[{"id":"https://openalex.org/I4210101778","display_name":"Samsung (United States)","ror":"https://ror.org/01bfbvm65","country_code":"US","type":"company","lineage":["https://openalex.org/I2250650973","https://openalex.org/I4210101778"]},{"id":"https://openalex.org/I4210139030","display_name":"Samsung (India)","ror":"https://ror.org/04cpx2569","country_code":"IN","type":"company","lineage":["https://openalex.org/I2250650973","https://openalex.org/I4210139030"]}],"countries":["IN","US"],"is_corresponding":false,"raw_author_name":"Manoi Goyal","raw_affiliation_strings":["OnDevice AI, Samsung R& D Institute, Bangalore, India","[Samsung]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"OnDevice AI, Samsung R& D Institute, Bangalore, India","institution_ids":["https://openalex.org/I4210139030"]},{"raw_affiliation_string":"[Samsung]","institution_ids":["https://openalex.org/I4210101778"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022341582","display_name":"Debi Prasanna Mohanty","orcid":"https://orcid.org/0000-0002-4248-0124"},"institutions":[{"id":"https://openalex.org/I4210101778","display_name":"Samsung (United States)","ror":"https://ror.org/01bfbvm65","country_code":"US","type":"company","lineage":["https://openalex.org/I2250650973","https://openalex.org/I4210101778"]},{"id":"https://openalex.org/I4210139030","display_name":"Samsung (India)","ror":"https://ror.org/04cpx2569","country_code":"IN","type":"company","lineage":["https://openalex.org/I2250650973","https://openalex.org/I4210139030"]}],"countries":["IN","US"],"is_corresponding":false,"raw_author_name":"Debi Prasanna Mohanty","raw_affiliation_strings":["OnDevice AI, Samsung R& D Institute, Bangalore, India","[Samsung]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"OnDevice AI, Samsung R& D Institute, Bangalore, India","institution_ids":["https://openalex.org/I4210139030"]},{"raw_affiliation_string":"[Samsung]","institution_ids":["https://openalex.org/I4210101778"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045185756","display_name":"Sukumar Moharana","orcid":null},"institutions":[{"id":"https://openalex.org/I4210101778","display_name":"Samsung (United States)","ror":"https://ror.org/01bfbvm65","country_code":"US","type":"company","lineage":["https://openalex.org/I2250650973","https://openalex.org/I4210101778"]},{"id":"https://openalex.org/I4210139030","display_name":"Samsung (India)","ror":"https://ror.org/04cpx2569","country_code":"IN","type":"company","lineage":["https://openalex.org/I2250650973","https://openalex.org/I4210139030"]}],"countries":["IN","US"],"is_corresponding":false,"raw_author_name":"Sukumar Moharana","raw_affiliation_strings":["OnDevice AI, Samsung R& D Institute, Bangalore, India","[Samsung]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"OnDevice AI, Samsung R& D Institute, Bangalore, India","institution_ids":["https://openalex.org/I4210139030"]},{"raw_affiliation_string":"[Samsung]","institution_ids":["https://openalex.org/I4210101778"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020182697","display_name":"Naresh Purre","orcid":null},"institutions":[{"id":"https://openalex.org/I4210101778","display_name":"Samsung (United States)","ror":"https://ror.org/01bfbvm65","country_code":"US","type":"company","lineage":["https://openalex.org/I2250650973","https://openalex.org/I4210101778"]},{"id":"https://openalex.org/I4210139030","display_name":"Samsung (India)","ror":"https://ror.org/04cpx2569","country_code":"IN","type":"company","lineage":["https://openalex.org/I2250650973","https://openalex.org/I4210139030"]}],"countries":["IN","US"],"is_corresponding":false,"raw_author_name":"Naresh Purre","raw_affiliation_strings":["OnDevice AI, Samsung R& D Institute, Bangalore, India","[Samsung]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"OnDevice AI, Samsung R& D Institute, Bangalore, India","institution_ids":["https://openalex.org/I4210139030"]},{"raw_affiliation_string":"[Samsung]","institution_ids":["https://openalex.org/I4210101778"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0941,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.3271491,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":93},"biblio":{"volume":null,"issue":null,"first_page":"5775","last_page":"5781"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing 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/T11105","display_name":"Advanced Image Processing 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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9959999918937683,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.993399977684021,"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/upsampling","display_name":"Upsampling","score":0.8888022899627686},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7999088764190674},{"id":"https://openalex.org/keywords/bicubic-interpolation","display_name":"Bicubic interpolation","score":0.783366322517395},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6432434916496277},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.628205418586731},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6258872747421265},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5432232022285461},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.5428663492202759},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.46428006887435913},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.4524267911911011},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.4149215519428253},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3830905556678772},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.36068230867385864},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.07935872673988342}],"concepts":[{"id":"https://openalex.org/C110384440","wikidata":"https://www.wikidata.org/wiki/Q1143270","display_name":"Upsampling","level":3,"score":0.8888022899627686},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7999088764190674},{"id":"https://openalex.org/C49608258","wikidata":"https://www.wikidata.org/wiki/Q611705","display_name":"Bicubic interpolation","level":4,"score":0.783366322517395},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6432434916496277},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.628205418586731},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6258872747421265},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5432232022285461},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.5428663492202759},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.46428006887435913},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.4524267911911011},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.4149215519428253},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3830905556678772},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.36068230867385864},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.07935872673988342},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C171836373","wikidata":"https://www.wikidata.org/wiki/Q2266329","display_name":"Linear interpolation","level":3,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/icpr48806.2021.9412222","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr48806.2021.9412222","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"},{"id":"pmh:oai:arXiv.org:2011.10251","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2011.10251","pdf_url":"https://arxiv.org/pdf/2011.10251","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"mag:3109202259","is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/2011.10251","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.2011.10251","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2011.10251","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article-journal"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2011.10251","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2011.10251","pdf_url":"https://arxiv.org/pdf/2011.10251","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":63,"referenced_works":["https://openalex.org/W54257720","https://openalex.org/W135113724","https://openalex.org/W603536130","https://openalex.org/W1491389626","https://openalex.org/W1885185971","https://openalex.org/W1910615622","https://openalex.org/W1971822075","https://openalex.org/W1981283549","https://openalex.org/W1998042868","https://openalex.org/W2008806374","https://openalex.org/W2022226704","https://openalex.org/W2087436818","https://openalex.org/W2088254198","https://openalex.org/W2099247484","https://openalex.org/W2099471712","https://openalex.org/W2099496146","https://openalex.org/W2103844245","https://openalex.org/W2111454493","https://openalex.org/W2118963448","https://openalex.org/W2127242687","https://openalex.org/W2144554289","https://openalex.org/W2157190232","https://openalex.org/W2157613008","https://openalex.org/W2161516371","https://openalex.org/W2164551808","https://openalex.org/W2165939075","https://openalex.org/W2172128189","https://openalex.org/W2194775991","https://openalex.org/W2214802144","https://openalex.org/W2242218935","https://openalex.org/W2503339013","https://openalex.org/W2607041014","https://openalex.org/W2734957715","https://openalex.org/W2747898905","https://openalex.org/W2778905022","https://openalex.org/W2780544323","https://openalex.org/W2792425829","https://openalex.org/W2891639959","https://openalex.org/W2902200975","https://openalex.org/W2902561591","https://openalex.org/W2946893679","https://openalex.org/W2962953661","https://openalex.org/W2963125871","https://openalex.org/W2963372104","https://openalex.org/W2963470893","https://openalex.org/W2963620158","https://openalex.org/W2964046669","https://openalex.org/W2964121744","https://openalex.org/W2969671163","https://openalex.org/W2999276659","https://openalex.org/W6602211262","https://openalex.org/W6618350375","https://openalex.org/W6629590909","https://openalex.org/W6631190155","https://openalex.org/W6649973027","https://openalex.org/W6676548197","https://openalex.org/W6679400994","https://openalex.org/W6683660953","https://openalex.org/W6691096134","https://openalex.org/W6724673846","https://openalex.org/W6726381175","https://openalex.org/W6740873641","https://openalex.org/W6756966161"],"related_works":["https://openalex.org/W3163486429","https://openalex.org/W3003166107","https://openalex.org/W3088734486","https://openalex.org/W2780963470","https://openalex.org/W3039219199","https://openalex.org/W3119712695","https://openalex.org/W2798877493","https://openalex.org/W2951071563","https://openalex.org/W3190162935","https://openalex.org/W3106758205","https://openalex.org/W3041819070","https://openalex.org/W3193888247","https://openalex.org/W3111025150","https://openalex.org/W3160337074","https://openalex.org/W2978361572","https://openalex.org/W3019481001","https://openalex.org/W2966380432","https://openalex.org/W2942655143","https://openalex.org/W2997806675","https://openalex.org/W3088065502"],"abstract_inverted_index":{"Recent":[0],"research":[1],"on":[2,32,59,92,112,150,171,183],"super-resolution":[3],"(SR)":[4],"has":[5,192],"witnessed":[6],"major":[7],"developments":[8],"with":[9,157],"the":[10,64,74,79,93,99,172,184],"advancements":[11],"of":[12,35,81,86,162,181,195],"deep":[13,124],"convolutional":[14],"neural":[15,125],"networks.":[16],"There":[17,102],"is":[18,52,95],"a":[19,96,110,122],"need":[20],"for":[21],"information":[22],"extraction":[23],"from":[24],"scenic":[25],"text":[26],"images":[27,31],"or":[28],"even":[29],"document":[30],"device,":[33],"most":[34],"which":[36,51],"are":[37,103],"low-resolution":[38],"(LR)":[39],"images.":[40,61],"Therefore,":[41],"SR":[42,90],"becomes":[43],"an":[44,158,178,193],"essential":[45],"pre-processing":[46],"step":[47],"as":[48],"Bicubic":[49],"Upsam-pling,":[50],"conventionally":[53],"present":[54,121],"in":[55,98,106,145],"smartphones,":[56],"performs":[57],"poorly":[58],"LR":[60],"To":[62],"give":[63],"user":[65],"more":[66],"control":[67],"over":[68,147],"his":[69],"privacy,":[70],"and":[71,84,108,132],"to":[72],"reduce":[73],"carbon":[75],"footprint":[76],"by":[77],"reducing":[78],"overhead":[80],"cloud":[82],"computing":[83],"hours":[85],"GPU":[87],"usage,":[88],"executing":[89],"models":[91],"edge":[94],"necessity":[97],"recent":[100],"times.":[101],"various":[104,151],"challenges":[105],"running":[107],"optimizing":[109],"model":[111],"resource-constrained":[113],"platforms":[114],"like":[115],"smartphones.":[116],"In":[117],"this":[118],"paper,":[119],"we":[120],"novel":[123],"network":[126],"that":[127],"reconstructs":[128],"sharper":[129],"character":[130],"edges":[131],"thus":[133],"boosts":[134],"OCR":[135,179],"confidence.":[136],"The":[137],"proposed":[138],"architecture":[139],"not":[140],"only":[141],"achieves":[142],"significant":[143],"improvement":[144],"PSNR":[146],"bicubic":[148],"upsampling":[149],"benchmark":[152],"datasets":[153],"but":[154],"also":[155,176],"runs":[156],"average":[159],"inference":[160],"time":[161],"11.7":[163],"ms":[164],"per":[165],"image.":[166],"We":[167,175],"have":[168],"outperformed":[169],"state-of-the-art":[170],"Text330":[173],"dataset.":[174],"achieve":[177],"accuracy":[180,194],"75.89%":[182],"ICDAR":[185],"2015":[186],"TextSR":[187],"dataset,":[188],"where":[189],"ground":[190],"truth":[191],"78.10%.":[196]},"counts_by_year":[{"year":2021,"cited_by_count":1}],"updated_date":"2026-07-03T08:13:44.112507","created_date":"2025-10-10T00:00:00"}