{"id":"https://openalex.org/W7131379680","doi":"https://doi.org/10.48550/arxiv.2602.19086","title":"Seal-Robust KCR: A Robust Kuzushiji Character Recognition Framework under Seal Interference","display_name":"Seal-Robust KCR: A Robust Kuzushiji Character Recognition Framework under Seal Interference","publication_year":2026,"publication_date":"2026-02-22","ids":{"openalex":"https://openalex.org/W7131379680","doi":"https://doi.org/10.48550/arxiv.2602.19086"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2602.19086","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.19086","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":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2602.19086","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5032044053","display_name":"Rui\u2010Yang Ju","orcid":"https://orcid.org/0000-0003-2240-1377"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ju, Rui-Yang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070945857","display_name":"Kohei Yamashita","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yamashita, Kohei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000531397","display_name":"Hirotaka Kameko","orcid":"https://orcid.org/0000-0001-9844-6198"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kameko, Hirotaka","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5101173515","display_name":"Shinsuke Mori","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mori, Shinsuke","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.984000027179718,"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":0.984000027179718,"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/T14319","display_name":"Currency Recognition and Detection","score":0.0013000000035390258,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.0010000000474974513,"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/glyph","display_name":"Glyph (data visualization)","score":0.6865000128746033},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.48429998755455017},{"id":"https://openalex.org/keywords/character-recognition","display_name":"Character recognition","score":0.4505999982357025},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.44429999589920044},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4374000132083893},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.41130000352859497},{"id":"https://openalex.org/keywords/character","display_name":"Character (mathematics)","score":0.38429999351501465},{"id":"https://openalex.org/keywords/intelligent-character-recognition","display_name":"Intelligent character recognition","score":0.34360000491142273},{"id":"https://openalex.org/keywords/precision-and-recall","display_name":"Precision and recall","score":0.3264000117778778}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7240999937057495},{"id":"https://openalex.org/C142816647","wikidata":"https://www.wikidata.org/wiki/Q5573018","display_name":"Glyph (data visualization)","level":3,"score":0.6865000128746033},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.583299994468689},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.48429998755455017},{"id":"https://openalex.org/C2987247673","wikidata":"https://www.wikidata.org/wiki/Q167555","display_name":"Character recognition","level":3,"score":0.4505999982357025},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.44429999589920044},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4374000132083893},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.41130000352859497},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.39899998903274536},{"id":"https://openalex.org/C2780861071","wikidata":"https://www.wikidata.org/wiki/Q1062934","display_name":"Character (mathematics)","level":2,"score":0.38429999351501465},{"id":"https://openalex.org/C44868376","wikidata":"https://www.wikidata.org/wiki/Q3099089","display_name":"Intelligent character recognition","level":4,"score":0.34360000491142273},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.3264000117778778},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.322299987077713},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.30709999799728394},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.3068000078201294},{"id":"https://openalex.org/C127705205","wikidata":"https://www.wikidata.org/wiki/Q5748245","display_name":"Heuristics","level":2,"score":0.30570000410079956},{"id":"https://openalex.org/C2778943297","wikidata":"https://www.wikidata.org/wiki/Q1079418","display_name":"Cursive","level":2,"score":0.29589998722076416},{"id":"https://openalex.org/C100660578","wikidata":"https://www.wikidata.org/wiki/Q18733","display_name":"Recall","level":2,"score":0.28999999165534973},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.289900004863739},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.2867000102996826},{"id":"https://openalex.org/C2781121862","wikidata":"https://www.wikidata.org/wiki/Q256","display_name":"Turkish","level":2,"score":0.28610000014305115},{"id":"https://openalex.org/C2777755289","wikidata":"https://www.wikidata.org/wiki/Q162919","display_name":"Seal (emblem)","level":2,"score":0.28290000557899475},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.27869999408721924},{"id":"https://openalex.org/C112640561","wikidata":"https://www.wikidata.org/wiki/Q2440634","display_name":"Handwriting recognition","level":3,"score":0.27619999647140503},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2759000062942505},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.2728999853134155},{"id":"https://openalex.org/C546480517","wikidata":"https://www.wikidata.org/wiki/Q167555","display_name":"Optical character recognition","level":3,"score":0.25870001316070557}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2602.19086","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.19086","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"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2602.19086","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.19086","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":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.5177250504493713,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Kuzushiji":[0,32,42],"was":[1],"one":[2],"of":[3,131,159,167,187],"the":[4,101,129,141,157,160,165,193,203],"most":[5,24],"widely":[6],"used":[7],"cursive":[8,18],"writing":[9],"systems":[10],"in":[11,63,163],"pre-modern":[12],"Japan.":[13],"Due":[14],"to":[15,30,71,108,127,149],"its":[16],"highly":[17],"forms":[19],"and":[20,99,143,177,189,197,199],"extensive":[21],"glyph":[22],"variations,":[23],"modern":[25],"Japanese":[26,55,64],"readers":[27],"are":[28],"unable":[29],"read":[31],"characters.":[33,83],"Consequently,":[34],"recent":[35],"studies":[36],"have":[37,48],"focused":[38],"on":[39,52,95,170,192,202],"developing":[40],"automated":[41],"character":[43,96,132,182],"recognition":[44,73,115],"(KCR)":[45],"methods,":[46],"which":[47],"achieved":[49],"strong":[50],"performance":[51,130],"relatively":[53],"clean":[54],"historical":[56,65],"document":[57,106],"images.":[58],"Although":[59],"seals":[60,80],"frequently":[61],"appear":[62],"documents,":[66],"existing":[67],"methods":[68],"often":[69],"fail":[70],"maintain":[72],"accuracy":[74],"under":[75],"seal":[76,110,152,168],"interference,":[77,111],"particularly":[78],"when":[79],"overlap":[81],"with":[82,173],"To":[84],"address":[85],"this":[86],"challenge,":[87],"we":[88,119],"propose":[89],"a":[90,121,145,174],"seal-robust":[91],"KCR":[92],"framework.":[93],"Based":[94],"detection,":[97],"classification,":[98],"ordering,":[100],"proposed":[102,161],"framework":[103,162],"additionally":[104],"incorporates":[105],"restoration":[107],"mitigate":[109],"thereby":[112],"improving":[113],"overall":[114],"performance.":[116],"In":[117],"addition,":[118],"introduce":[120],"novel":[122],"synthetic":[123,146,204],"data":[124],"augmentation":[125],"strategy":[126],"enhance":[128],"detection":[133],"models.":[134],"We":[135],"further":[136],"correct":[137],"annotation":[138],"errors,":[139],"reconstruct":[140],"dataset,":[142],"create":[144],"test":[147,195,205],"set":[148],"simulate":[150],"severe":[151],"interference.":[153],"Experimental":[154],"results":[155],"demonstrate":[156],"effectiveness":[158],"mitigating":[164],"impact":[166],"interference":[169],"KCR.":[171],"Compared":[172],"conventional":[175],"baseline":[176],"NDLkotenOCR,":[178],"it":[179],"achieves":[180],"relative":[181],"error":[183],"rate":[184],"(CER)":[185],"reductions":[186],"39.7%":[188],"5.9%,":[190],"respectively,":[191,201],"real":[194],"set,":[196],"50.1%":[198],"41.7%,":[200],"set.":[206]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-02-26T00:00:00"}