{"id":"https://openalex.org/W7164182334","doi":"https://doi.org/10.1109/access.2026.3702163","title":"AeroBlade-STR: Efficient Scene Text Recognition for Aviation Engine Blade Identification Codes","display_name":"AeroBlade-STR: Efficient Scene Text Recognition for Aviation Engine Blade Identification Codes","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7164182334","doi":"https://doi.org/10.1109/access.2026.3702163"},"language":"en","primary_location":{"id":"doi:10.1109/access.2026.3702163","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3702163","pdf_url":null,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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://doi.org/10.1109/access.2026.3702163","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5138289880","display_name":"Yalan Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I58995867","display_name":"Civil Aviation Flight University of China","ror":"https://ror.org/01xyb1v19","country_code":"CN","type":"education","lineage":["https://openalex.org/I58995867"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yalan Zhang","raw_affiliation_strings":["College of Computer, Civil Aviation Flight University of China, Deyang, China"],"raw_orcid":"https://orcid.org/0009-0003-7939-3977","affiliations":[{"raw_affiliation_string":"College of Computer, Civil Aviation Flight University of China, Deyang, China","institution_ids":["https://openalex.org/I58995867"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138323480","display_name":"Rui Wan","orcid":"https://orcid.org/0009-0007-6827-8008"},"institutions":[{"id":"https://openalex.org/I58995867","display_name":"Civil Aviation Flight University of China","ror":"https://ror.org/01xyb1v19","country_code":"CN","type":"education","lineage":["https://openalex.org/I58995867"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rui Wan","raw_affiliation_strings":["College of Computer, Civil Aviation Flight University of China, Deyang, China"],"raw_orcid":"https://orcid.org/0009-0007-6827-8008","affiliations":[{"raw_affiliation_string":"College of Computer, Civil Aviation Flight University of China, Deyang, China","institution_ids":["https://openalex.org/I58995867"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5138324003","display_name":"Fangliu","orcid":null},"institutions":[{"id":"https://openalex.org/I58995867","display_name":"Civil Aviation Flight University of China","ror":"https://ror.org/01xyb1v19","country_code":"CN","type":"education","lineage":["https://openalex.org/I58995867"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fang Liu","raw_affiliation_strings":["College of Computer, Civil Aviation Flight University of China, Deyang, China"],"raw_orcid":"https://orcid.org/0009-0009-3054-8679","affiliations":[{"raw_affiliation_string":"College of Computer, Civil Aviation Flight University of China, Deyang, China","institution_ids":["https://openalex.org/I58995867"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I58995867"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.74431654,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"14","issue":null,"first_page":"99626","last_page":"99635"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.34119999408721924,"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":0.34119999408721924,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.04910000041127205,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.025800000876188278,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/identification","display_name":"Identification (biology)","score":0.666100025177002},{"id":"https://openalex.org/keywords/blade","display_name":"Blade (archaeology)","score":0.4903999865055084},{"id":"https://openalex.org/keywords/aviation","display_name":"Aviation","score":0.44510000944137573},{"id":"https://openalex.org/keywords/text-recognition","display_name":"Text recognition","score":0.4187999963760376},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.39629998803138733},{"id":"https://openalex.org/keywords/cognitive-neuroscience-of-visual-object-recognition","display_name":"Cognitive neuroscience of visual object recognition","score":0.37540000677108765}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.760200023651123},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.666100025177002},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5034000277519226},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5024999976158142},{"id":"https://openalex.org/C2776132848","wikidata":"https://www.wikidata.org/wiki/Q3045036","display_name":"Blade (archaeology)","level":2,"score":0.4903999865055084},{"id":"https://openalex.org/C74448152","wikidata":"https://www.wikidata.org/wiki/Q765633","display_name":"Aviation","level":2,"score":0.44510000944137573},{"id":"https://openalex.org/C2983812711","wikidata":"https://www.wikidata.org/wiki/Q167555","display_name":"Text recognition","level":3,"score":0.4187999963760376},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4174000024795532},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.39629998803138733},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.37540000677108765},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37450000643730164},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.28940001130104065},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.2662000060081482},{"id":"https://openalex.org/C199639397","wikidata":"https://www.wikidata.org/wiki/Q1788588","display_name":"Engineering drawing","level":1,"score":0.2581000030040741}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2026.3702163","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3702163","pdf_url":null,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:bc7f060217644518afaa172405b0fa8c","is_oa":false,"landing_page_url":"https://doaj.org/article/bc7f060217644518afaa172405b0fa8c","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 14, Pp 99626-99635 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2026.3702163","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3702163","pdf_url":null,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Accurate":[0],"identification":[1,4],"of":[2,16,135,151,180,186,192,201],"surface":[3,38],"codes":[5],"on":[6,62,111,168],"aircraft":[7],"engine":[8],"blades":[9],"is":[10],"critical":[11],"for":[12],"the":[13,48,63,105,126,162,197],"effective":[14],"management":[15],"their":[17],"full":[18],"lifecycle.":[19],"However,":[20],"conventional":[21],"optical":[22],"character":[23],"recognition":[24,58,152,178,203],"methods":[25],"encounter":[26],"considerable":[27],"challenges":[28,49],"due":[29],"to":[30,46,103,161],"factors":[31],"such":[32],"as":[33],"high-temperature":[34],"oxidation,":[35],"mechanical":[36],"wear,":[37],"deformation,":[39],"and":[40,96,123,156,189,199],"complex":[41],"imaging":[42],"conditions.":[43],"In":[44],"order":[45],"address":[47],"identified,":[50],"this":[51],"paper":[52],"proposes":[53],"an":[54,132],"enhanced":[55],"scene":[56],"text":[57,202],"framework,":[59],"AeroBlade-STR,":[60],"based":[61],"SVTRv2":[64],"model.":[65],"The":[66,141],"proposed":[67],"framework":[68],"enhances":[69],"spatial":[70],"perception":[71],"through":[72],"a":[73,83,91,98,177,183],"hybrid":[74],"coordinate":[75],"attention":[76],"mechanism,":[77],"improves":[78],"local":[79],"detail":[80],"modelling":[81],"with":[82,182],"dynamic":[84],"convolutional":[85],"module,":[86,95],"addresses":[87],"scale":[88],"diversity":[89],"via":[90],"multi-scale":[92],"feature":[93],"fusion":[94],"introduces":[97],"focused":[99],"CTC":[100],"loss":[101],"function":[102],"mitigate":[104],"easy-hard":[106],"sample":[107],"imbalance":[108],"problem.":[109],"Experiments":[110],"multiple":[112],"public":[113],"benchmark":[114],"datasets,":[115],"including":[116],"IIIT5k,":[117],"SVT,":[118],"ICDAR2013":[119],"(IC13),":[120],"ICDAR2015":[121],"(IC15),":[122],"SVTP,":[124],"demonstrate":[125],"method's":[127],"outstanding":[128],"generalization":[129],"capability,":[130],"achieving":[131],"average":[133],"accuracy":[134,179],"95.9%":[136],"\u2014":[137],"reaching":[138],"industry-leading":[139],"levels.":[140],"findings":[142],"indicate":[143],"that":[144],"AeroBlade-STR":[145],"exhibits":[146],"strong":[147],"performance":[148],"in":[149,204],"terms":[150],"accuracy,":[153],"model":[154,184],"complexity,":[155],"inference":[157],"efficiency":[158],"when":[159],"compared":[160],"prevailing":[163],"mainstream":[164],"approach":[165],"SVTRv2-B.":[166],"Specifically,":[167],"our":[169,174],"self-built":[170],"dataset":[171],"(Aero-BladeText,":[172],"ABText),":[173],"method":[175],"achieves":[176],"93.2%":[181],"size":[185],"22.9M":[187],"parameters":[188],"computational":[190],"cost":[191],"140.4":[193],"GFLOPs,":[194],"thereby":[195],"enhancing":[196],"robustness":[198],"practicality":[200],"industrial":[205],"scenarios.":[206]},"counts_by_year":[],"updated_date":"2026-07-08T06:17:01.165560","created_date":"2026-06-11T00:00:00"}
