{"id":"https://openalex.org/W2936226716","doi":"https://doi.org/10.1109/access.2019.2908933","title":"FTPN: Scene Text Detection With Feature Pyramid Based Text Proposal Network","display_name":"FTPN: Scene Text Detection With Feature Pyramid Based Text Proposal Network","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2936226716","doi":"https://doi.org/10.1109/access.2019.2908933","mag":"2936226716"},"language":"en","primary_location":{"id":"doi:10.1109/access.2019.2908933","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2908933","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08682040.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08682040.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5005463262","display_name":"Fagui Liu","orcid":"https://orcid.org/0000-0003-1135-4982"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Fagui Liu","raw_affiliation_strings":["School of Computer Science and Engineering, South China University of Technology, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102931127","display_name":"Cheng Chen","orcid":"https://orcid.org/0000-0003-0128-5821"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cheng Chen","raw_affiliation_strings":["School of Computer Science and Engineering, South China University of Technology, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-0128-5821","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068056559","display_name":"Dian Gu","orcid":"https://orcid.org/0000-0002-8875-7491"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dian Gu","raw_affiliation_strings":["School of Computer Science and Engineering, South China University of Technology, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103057082","display_name":"Jingzhong Zheng","orcid":"https://orcid.org/0000-0002-5248-7354"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingzhong Zheng","raw_affiliation_strings":["School of Computer Science and Engineering, South China University of Technology, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5005463262"],"corresponding_institution_ids":["https://openalex.org/I90610280"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":2.4494,"has_fulltext":true,"cited_by_count":34,"citation_normalized_percentile":{"value":0.91422044,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"7","issue":null,"first_page":"44219","last_page":"44228"},"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/T12707","display_name":"Vehicle License Plate Recognition","score":0.9933000206947327,"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/T14339","display_name":"Image Processing and 3D Reconstruction","score":0.9818000197410583,"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":0.8508759140968323},{"id":"https://openalex.org/keywords/text-detection","display_name":"Text detection","score":0.6887046098709106},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.679760217666626},{"id":"https://openalex.org/keywords/pyramid","display_name":"Pyramid (geometry)","score":0.6464880704879761},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6088800430297852},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5842019319534302},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5070044994354248},{"id":"https://openalex.org/keywords/text-recognition","display_name":"Text recognition","score":0.4853457510471344},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.4692015051841736},{"id":"https://openalex.org/keywords/encode","display_name":"ENCODE","score":0.4464956521987915},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.4304355978965759},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.42786216735839844},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.33429503440856934},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.32397300004959106},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.19199758768081665}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8508759140968323},{"id":"https://openalex.org/C2983589003","wikidata":"https://www.wikidata.org/wiki/Q167555","display_name":"Text detection","level":3,"score":0.6887046098709106},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.679760217666626},{"id":"https://openalex.org/C142575187","wikidata":"https://www.wikidata.org/wiki/Q3358290","display_name":"Pyramid (geometry)","level":2,"score":0.6464880704879761},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6088800430297852},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5842019319534302},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5070044994354248},{"id":"https://openalex.org/C2983812711","wikidata":"https://www.wikidata.org/wiki/Q167555","display_name":"Text recognition","level":3,"score":0.4853457510471344},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.4692015051841736},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.4464956521987915},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.4304355978965759},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.42786216735839844},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.33429503440856934},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.32397300004959106},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.19199758768081665},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2019.2908933","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2908933","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08682040.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:f0c900e309934931bc1c2b0960d7af2b","is_oa":true,"landing_page_url":"https://doaj.org/article/f0c900e309934931bc1c2b0960d7af2b","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 7, Pp 44219-44228 (2019)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2019.2908933","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2908933","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08682040.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2936226716.pdf","grobid_xml":"https://content.openalex.org/works/W2936226716.grobid-xml"},"referenced_works_count":50,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W654550266","https://openalex.org/W1488125194","https://openalex.org/W1686810756","https://openalex.org/W1903029394","https://openalex.org/W1935817682","https://openalex.org/W1972065312","https://openalex.org/W2008806374","https://openalex.org/W2009854331","https://openalex.org/W2019478948","https://openalex.org/W2047695704","https://openalex.org/W2056518953","https://openalex.org/W2128854450","https://openalex.org/W2131163834","https://openalex.org/W2142159465","https://openalex.org/W2144554289","https://openalex.org/W2148214126","https://openalex.org/W2150259535","https://openalex.org/W2152696939","https://openalex.org/W2163605009","https://openalex.org/W2165401735","https://openalex.org/W2194187530","https://openalex.org/W2194775991","https://openalex.org/W2217433794","https://openalex.org/W2239285313","https://openalex.org/W2263734677","https://openalex.org/W2339589954","https://openalex.org/W2519818067","https://openalex.org/W2533962510","https://openalex.org/W2550687635","https://openalex.org/W2565591417","https://openalex.org/W2565639579","https://openalex.org/W2593539516","https://openalex.org/W2604243686","https://openalex.org/W2604300598","https://openalex.org/W2784050770","https://openalex.org/W2790046311","https://openalex.org/W2913573645","https://openalex.org/W2953384591","https://openalex.org/W2963517393","https://openalex.org/W3102695566","https://openalex.org/W3106228955","https://openalex.org/W3106250896","https://openalex.org/W6629021407","https://openalex.org/W6642972425","https://openalex.org/W6682305768","https://openalex.org/W6684191040","https://openalex.org/W6713134421","https://openalex.org/W6729791593","https://openalex.org/W6785652829"],"related_works":["https://openalex.org/W4312663241","https://openalex.org/W3103048049","https://openalex.org/W4221004363","https://openalex.org/W3113266311","https://openalex.org/W2963299604","https://openalex.org/W3211262047","https://openalex.org/W950386562","https://openalex.org/W3012395971","https://openalex.org/W2363517123","https://openalex.org/W2894624991"],"abstract_inverted_index":{"Scene":[0],"text":[1,10,24,45,61,121,131,141,146],"detection":[2,46,62],"is":[3,160],"to":[4,40,78,81,97,111,115,153],"detect":[5],"the":[6,12,15,22,48,66,94,102,120,125,189,195],"position":[7],"of":[8,17,101,119,130,197],"a":[9,53,128,140,144],"in":[11,31,47,83,93],"natural":[13],"scene,":[14],"quality":[16],"which":[18,148,193],"will":[19],"directly":[20],"affect":[21],"subsequent":[23],"recognition.":[25],"It":[26],"plays":[27],"an":[28,58],"important":[29],"role":[30],"fields":[32],"such":[33],"as":[34,52,127],"image":[35],"retrieval":[36],"and":[37,43,71,168,172,178],"autopilot.":[38],"How":[39],"perform":[41],"multi-scale":[42,99],"multi-oriented":[44],"scene":[49,60],"still":[50],"remains":[51],"problem.":[54],"This":[55],"paper":[56],"proposes":[57],"effective":[59],"method":[63,159,183],"that":[64],"combines":[65],"convolutional":[67],"neural":[68,73],"network":[69,74],"(CNN)":[70],"recurrent":[72],"(RNN).":[75],"In":[76],"order":[77],"better":[79],"adapt":[80],"texts":[82],"different":[84],"scales,":[85],"feature":[86],"pyramid":[87],"networks":[88],"(FPN)":[89],"have":[90,175],"been":[91],"applied":[92],"CNN":[95],"part":[96],"extract":[98],"features":[100,114],"image.":[103],"We":[104],"then":[105],"utilize":[106],"bidirectional":[107],"long-short-term":[108],"memory":[109],"(Bi-LSTM)":[110],"encode":[112],"these":[113],"make":[116],"full":[117],"use":[118],"sequence":[122],"characteristics":[123],"with":[124],"outputs":[126],"series":[129],"proposals.":[132],"The":[133,157],"generated":[134],"proposals":[135],"are":[136],"finally":[137],"linked":[138],"into":[139],"line":[142],"through":[143],"well-designed":[145],"connector,":[147],"can":[149],"be":[150],"flexibly":[151],"adapted":[152],"any":[154],"oriented":[155],"texts.":[156],"proposed":[158],"evaluated":[161],"on":[162,188],"three":[163],"public":[164],"datasets:":[165],"ICDAR2013,":[166],"ICDAR2015,":[167],"USTB-SV1K.":[169],"For":[170],"ICDAR2013":[171],"USTB-1K,":[173],"we":[174],"reached":[176,185],"92.5%":[177],"62.6%":[179],"F-measure,":[180],"respectively.":[181],"Our":[182],"has":[184],"72.8%":[186],"F-measure":[187],"more":[190],"challenging":[191],"ICDAR2015":[192],"demonstrates":[194],"effectiveness":[196],"our":[198],"method.":[199]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":9},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":3}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}