{"id":"https://openalex.org/W7164021025","doi":"https://doi.org/10.48550/arxiv.2606.09446","title":"Leveraging Morphology for Historical Script Metrological Analysis","display_name":"Leveraging Morphology for Historical Script Metrological Analysis","publication_year":2026,"publication_date":"2026-06-08","ids":{"openalex":"https://openalex.org/W7164021025","doi":"https://doi.org/10.48550/arxiv.2606.09446"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.09446","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.09446","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":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2606.09446","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5135132209","display_name":"Efstathiou, Malamatenia, Vlachou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Efstathiou, Malamatenia Vlachou","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133201326","display_name":"Raphael Baena","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Baena, Rapha\u00ebl","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138237818","display_name":"Dominique Stutzmann","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Stutzmann, Dominique","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5061634216","display_name":"Mathieu Aubry","orcid":"https://orcid.org/0000-0002-3804-0193"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Aubry, Mathieu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"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":0.9815999865531921,"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":0.9815999865531921,"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/T14339","display_name":"Image Processing and 3D Reconstruction","score":0.008700000122189522,"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/T12377","display_name":"Digital Humanities and Scholarship","score":0.0019000000320374966,"subfield":{"id":"https://openalex.org/subfields/1208","display_name":"Literature and Literary Theory"},"field":{"id":"https://openalex.org/fields/12","display_name":"Arts and Humanities"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.5508999824523926},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.5483999848365784},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.4957999885082245},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.48240000009536743},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.47850000858306885},{"id":"https://openalex.org/keywords/transcription","display_name":"Transcription (linguistics)","score":0.45809999108314514},{"id":"https://openalex.org/keywords/data-visualization","display_name":"Data visualization","score":0.4187000095844269},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.4072999954223633}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7512000203132629},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.5508999824523926},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.5483999848365784},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5396999716758728},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.4957999885082245},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.48240000009536743},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.47850000858306885},{"id":"https://openalex.org/C179926584","wikidata":"https://www.wikidata.org/wiki/Q207714","display_name":"Transcription (linguistics)","level":2,"score":0.45809999108314514},{"id":"https://openalex.org/C172367668","wikidata":"https://www.wikidata.org/wiki/Q6504956","display_name":"Data visualization","level":3,"score":0.4187000095844269},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.4072999954223633},{"id":"https://openalex.org/C61423126","wikidata":"https://www.wikidata.org/wiki/Q187432","display_name":"Scripting language","level":2,"score":0.39989998936653137},{"id":"https://openalex.org/C147037132","wikidata":"https://www.wikidata.org/wiki/Q6865426","display_name":"Minimum bounding box","level":3,"score":0.39899998903274536},{"id":"https://openalex.org/C2780861071","wikidata":"https://www.wikidata.org/wiki/Q1062934","display_name":"Character (mathematics)","level":2,"score":0.33059999346733093},{"id":"https://openalex.org/C63584917","wikidata":"https://www.wikidata.org/wiki/Q333286","display_name":"Bounding overwatch","level":2,"score":0.32659998536109924},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.32199999690055847},{"id":"https://openalex.org/C155846161","wikidata":"https://www.wikidata.org/wiki/Q1143367","display_name":"Graphical model","level":2,"score":0.289900004863739},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.27970001101493835},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.2615000009536743},{"id":"https://openalex.org/C546480517","wikidata":"https://www.wikidata.org/wiki/Q167555","display_name":"Optical character recognition","level":3,"score":0.25999999046325684},{"id":"https://openalex.org/C45235069","wikidata":"https://www.wikidata.org/wiki/Q278425","display_name":"Table (database)","level":2,"score":0.25279998779296875},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.2500999867916107}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.09446","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.09446","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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.09446","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.09446","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":"Preprint"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.8344736099243164,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Advances":[0],"in":[1,39,166,220],"handwritten":[2],"text":[3,231],"recognition":[4],"have":[5],"enabled":[6,139],"large-scale":[7],"transcription":[8,106],"of":[9,25,53,136,158,214,222,230,240],"historical":[10,26],"documents,":[11],"but":[12,200],"still":[13],"provide":[14],"limited":[15],"access":[16],"to":[17,43,75,179,196,202,234],"interpretable":[18],"visual":[19],"measurements":[20,138,185,237],"for":[21,125,143],"paleography,":[22],"the":[23,41,51,111,133,156,159,167,212,241],"study":[24,210],"scripts.":[27],"In":[28],"this":[29,152],"paper,":[30],"our":[31,141,184,215,236],"main":[32],"insight":[33],"is":[34,232],"that":[35,98],"morphological":[36],"script":[37],"analysis,":[38],"particular":[40],"capacity":[42],"learn":[44,76],"character":[45,101,118],"prototypes":[46],"from":[47],"line-level":[48,105],"transcriptions,":[49],"enables":[50,99],"definition":[52],"scalable,":[54],"meaningful,":[55],"and":[56,79,83,95,115,131,146,174,204,217,245],"stable":[57],"paleographic":[58,126],"measurements.":[59,127],"More":[60],"precisely,":[61],"we":[62,90,129,154],"leverage":[63],"a":[64,70,92,227],"transformer-based":[65],"detection":[66],"architecture":[67,94,142],"together":[68],"with":[69,103],"prototype-based":[71],"line":[72],"reconstruction":[73],"module":[74],"prototypical":[77],"characters":[78],"their":[80],"occurrence,":[81],"deformation,":[82],"positioning.":[84],"Our":[85],"contributions":[86],"are":[87,247],"twofold.":[88],"First,":[89],"introduce":[91,130],"deep":[93],"learning":[96],"methodology":[97],"efficient":[100],"modeling":[102],"only":[104,195],"supervision,":[107],"significantly":[108],"improving":[109],"over":[110,186],"Learnable":[112],"Typewriter":[113],"baseline":[114],"enabling":[116],"accurate":[117],"bounding":[119],"box":[120],"prediction,":[121],"unlocking":[122],"its":[123,218],"potential":[124],"Second,":[128],"demonstrate":[132],"paleographical":[134],"relevance":[135],"automatic":[137],"by":[140,171,176],"characters,":[144],"bi-grams,":[145],"spaces":[147],"between":[148],"graphical":[149,198],"units.":[150],"For":[151],"demonstration,":[153],"extend":[155],"annotations":[157],"codex":[160],"Paris,":[161],"BnF,":[162],"fr.":[163],"2813,":[164],"commissioned":[165],"late":[168],"fourteenth":[169],"century":[170],"Charles":[172],"V":[173],"copied":[175],"four":[177],"hands,":[178],"160":[180,242],"pages.":[181,243],"We":[182],"visualize":[183],"these":[187],"pages,":[188],"showing":[189],"how":[190],"they":[191],"enable":[192],"us":[193],"not":[194],"differentiate":[197],"profiles,":[199],"also":[201],"discover":[203],"analyze":[205],"subtle":[206],"variations.":[207],"This":[208],"case":[209],"outlines":[211],"scalability":[213],"approach":[216],"frugality":[219],"terms":[221],"required":[223],"training":[224],"data,":[225],"since":[226],"single":[228],"column":[229],"sufficient":[233],"compute":[235],"on":[238],"each":[239],"Data":[244],"code":[246],"publicly":[248],"available":[249],"at:":[250],"https://malamatenia.github.io/morphology4metrology-analysis.":[251]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-10T00:00:00"}
