{"id":"https://openalex.org/W4200085722","doi":"https://doi.org/10.1109/gcce53005.2021.9621914","title":"Text Image Super Resolution Using Deep Attention Neural Network","display_name":"Text Image Super Resolution Using Deep Attention Neural Network","publication_year":2021,"publication_date":"2021-10-12","ids":{"openalex":"https://openalex.org/W4200085722","doi":"https://doi.org/10.1109/gcce53005.2021.9621914"},"language":"en","primary_location":{"id":"doi:10.1109/gcce53005.2021.9621914","is_oa":false,"landing_page_url":"https://doi.org/10.1109/gcce53005.2021.9621914","pdf_url":null,"source":{"id":"https://openalex.org/S4363607807","display_name":"2021 IEEE 10th Global Conference on Consumer Electronics (GCCE)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE 10th Global Conference on Consumer Electronics (GCCE)","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/A5056961910","display_name":"Yun Liu","orcid":"https://orcid.org/0000-0001-6143-0264"},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yun Liu","raw_affiliation_strings":["Graduate School of Fundamental Science and Engineering, Waseda University, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Fundamental Science and Engineering, Waseda University, Tokyo, Japan","institution_ids":["https://openalex.org/I150744194"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041873783","display_name":"Remina Yano","orcid":null},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Remina Yano","raw_affiliation_strings":["Graduate School of Fundamental Science and Engineering, Waseda University, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Fundamental Science and Engineering, Waseda University, Tokyo, Japan","institution_ids":["https://openalex.org/I150744194"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025914451","display_name":"Hiroshi Watanabe","orcid":"https://orcid.org/0000-0003-1557-3015"},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hiroshi Watanabe","raw_affiliation_strings":["Graduate School of Fundamental Science and Engineering, Waseda University, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Fundamental Science and Engineering, Waseda University, Tokyo, Japan","institution_ids":["https://openalex.org/I150744194"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054231771","display_name":"Takuya Suzuki","orcid":"https://orcid.org/0000-0001-7692-9447"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Takuya Suzuki","raw_affiliation_strings":["SHARP Corporation, Chiba, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SHARP Corporation, Chiba, Japan","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082382200","display_name":"Takeshi Chujoh","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Takeshi Chujoh","raw_affiliation_strings":["SHARP Corporation, Chiba, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SHARP Corporation, Chiba, Japan","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007097287","display_name":"Tomohiro Ikai","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tomohiro Ikai","raw_affiliation_strings":["SHARP Corporation, Chiba, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SHARP Corporation, Chiba, Japan","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0656,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.33911175,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"280","last_page":"282"},"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":0.9983000159263611,"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/T10531","display_name":"Advanced Vision and Imaging","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"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7909367084503174},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7692584991455078},{"id":"https://openalex.org/keywords/bicubic-interpolation","display_name":"Bicubic interpolation","score":0.6885591745376587},{"id":"https://openalex.org/keywords/optical-character-recognition","display_name":"Optical character recognition","score":0.685248076915741},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6348670125007629},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5995514988899231},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5834411978721619},{"id":"https://openalex.org/keywords/resolution","display_name":"Resolution (logic)","score":0.5357156991958618},{"id":"https://openalex.org/keywords/low-resolution","display_name":"Low resolution","score":0.5329262614250183},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.5310920476913452},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.5239006280899048},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5120270848274231},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.44526615738868713},{"id":"https://openalex.org/keywords/character","display_name":"Character (mathematics)","score":0.4391981065273285},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4361634850502014},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.4288361966609955},{"id":"https://openalex.org/keywords/high-resolution","display_name":"High resolution","score":0.30698418617248535},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11140140891075134}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7909367084503174},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7692584991455078},{"id":"https://openalex.org/C49608258","wikidata":"https://www.wikidata.org/wiki/Q611705","display_name":"Bicubic interpolation","level":4,"score":0.6885591745376587},{"id":"https://openalex.org/C546480517","wikidata":"https://www.wikidata.org/wiki/Q167555","display_name":"Optical character recognition","level":3,"score":0.685248076915741},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6348670125007629},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5995514988899231},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5834411978721619},{"id":"https://openalex.org/C138268822","wikidata":"https://www.wikidata.org/wiki/Q1051925","display_name":"Resolution (logic)","level":2,"score":0.5357156991958618},{"id":"https://openalex.org/C3019883945","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Low resolution","level":3,"score":0.5329262614250183},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.5310920476913452},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.5239006280899048},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5120270848274231},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.44526615738868713},{"id":"https://openalex.org/C2780861071","wikidata":"https://www.wikidata.org/wiki/Q1062934","display_name":"Character (mathematics)","level":2,"score":0.4391981065273285},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4361634850502014},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.4288361966609955},{"id":"https://openalex.org/C3020199158","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"High resolution","level":2,"score":0.30698418617248535},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11140140891075134},{"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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/gcce53005.2021.9621914","is_oa":false,"landing_page_url":"https://doi.org/10.1109/gcce53005.2021.9621914","pdf_url":null,"source":{"id":"https://openalex.org/S4363607807","display_name":"2021 IEEE 10th Global Conference on Consumer Electronics (GCCE)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE 10th Global Conference on Consumer Electronics (GCCE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W1885185971","https://openalex.org/W2103261301","https://openalex.org/W2242218935","https://openalex.org/W2866634454","https://openalex.org/W2884585870","https://openalex.org/W2963420686","https://openalex.org/W2963470893","https://openalex.org/W6753412334"],"related_works":["https://openalex.org/W3098848838","https://openalex.org/W3163125609","https://openalex.org/W4296995023","https://openalex.org/W2070173637","https://openalex.org/W3118545013","https://openalex.org/W1516116847","https://openalex.org/W4200085722","https://openalex.org/W2115780304","https://openalex.org/W2412281349","https://openalex.org/W4212954839"],"abstract_inverted_index":{"In":[0,49],"this":[1],"paper,":[2],"we":[3,53,69],"propose":[4,70],"a":[5,71],"super-resolution":[6],"method":[7,91],"for":[8],"text":[9,41,60,86],"images":[10,61,87],"to":[11,27,38],"improve":[12],"the":[13,28,31,50,82,98,106,111],"accuracy":[14,21,84],"of":[15,22,30,85,97,108],"optical":[16],"character":[17],"recognition":[18,83],"(OCR).":[19],"The":[20],"OCR":[23,35],"is":[24,36,92],"closely":[25],"related":[26],"resolution":[29,40],"image,":[32],"and":[33,65,102,110],"when":[34],"applied":[37],"low":[39],"images,":[42,101],"satisfactory":[43],"results":[44,79,107],"are":[45],"often":[46],"not":[47],"obtained.":[48],"proposed":[51],"method,":[52],"extract":[54],"more":[55],"representative":[56],"feature":[57],"information":[58],"from":[59],"by":[62,88],"combining":[63],"channel":[64],"spatial":[66],"attention.":[67],"Furthermore,":[68],"new":[72],"loss":[73],"function":[74],"called":[75],"\u201cedge":[76],"loss\u201d.":[77],"Experimental":[78],"show":[80],"that":[81,96],"our":[89],"SR":[90],"5.87%":[93],"higher":[94,104],"than":[95,105],"original":[99],"low-resolution":[100],"also":[103],"BICUBIC":[109],"baseline":[112],"model.":[113]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
