{"id":"https://openalex.org/W6929480683","doi":"https://doi.org/10.48550/arxiv.2409.08573","title":"HTR-VT: Handwritten Text Recognition with Vision Transformer","display_name":"HTR-VT: Handwritten Text Recognition with Vision Transformer","publication_year":2024,"publication_date":"2024-09-13","ids":{"openalex":"https://openalex.org/W6929480683","doi":"https://doi.org/10.48550/arxiv.2409.08573"},"language":"en","primary_location":{"id":"doi:10.48550/arxiv.2409.08573","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2409.08573","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-journal"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2409.08573","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Li, Yuting","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Li, Yuting","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Chen, Dexiong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Dexiong","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Tang, Tinglong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tang, Tinglong","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Shen, Xi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shen, Xi","raw_affiliation_strings":[],"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":true,"primary_topic":{"id":"https://openalex.org/T10725","display_name":"RNA Interference and Gene Delivery","score":0.1923999935388565,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10725","display_name":"RNA Interference and Gene Delivery","score":0.1923999935388565,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10604","display_name":"RNA Research and Splicing","score":0.07559999823570251,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T13326","display_name":"Biochemical and Structural Characterization","score":0.07410000264644623,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.6154000163078308},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.5870000123977661},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5802000164985657},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5385000109672546},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5037999749183655},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4830999970436096},{"id":"https://openalex.org/keywords/minification","display_name":"Minification","score":0.4366999864578247},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.426800012588501},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4153999984264374}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7856000065803528},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.6154000163078308},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5870000123977661},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5802000164985657},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5684999823570251},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5385000109672546},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5037999749183655},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4830999970436096},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.4366999864578247},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.426800012588501},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4153999984264374},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.40610000491142273},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3930000066757202},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.361299991607666},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3522999882698059},{"id":"https://openalex.org/C186633575","wikidata":"https://www.wikidata.org/wiki/Q845060","display_name":"Maxima and minima","level":2,"score":0.34869998693466187},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.3411000072956085},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.32280001044273376},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.3095000088214874},{"id":"https://openalex.org/C2983589003","wikidata":"https://www.wikidata.org/wiki/Q167555","display_name":"Text detection","level":3,"score":0.302700012922287},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.28780001401901245},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.28700000047683716},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.28360000252723694},{"id":"https://openalex.org/C2983812711","wikidata":"https://www.wikidata.org/wiki/Q167555","display_name":"Text recognition","level":3,"score":0.26660001277923584},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.26330000162124634},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.2615000009536743},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.26109999418258667},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.25450000166893005},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.2535000145435333}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2409.08573","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2409.08573","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-journal"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2409.08573","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2409.08573","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-journal"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"We":[0,64],"explore":[1],"the":[2,58,61,78,91,106,115,146,150],"application":[3],"of":[4,15,60,77,105],"Vision":[5],"Transformer":[6],"(ViT)":[7],"for":[8,23,73],"handwritten":[9],"text":[10,156],"recognition.":[11],"The":[12,158],"limited":[13],"availability":[14],"labeled":[16],"data":[17,36],"in":[18,114],"this":[19,47],"domain":[20],"poses":[21],"challenges":[22],"achieving":[24],"high":[25],"performance":[26],"solely":[27],"relying":[28],"on":[29,40,132,145],"ViT.":[30],"Previous":[31],"transformer-based":[32],"models":[33,131],"required":[34],"external":[35],"or":[37],"extensive":[38],"pre-training":[39],"large":[41],"datasets":[42,134],"to":[43,88],"excel.":[44],"To":[45],"address":[46],"limitation,":[48],"we":[49],"introduce":[50],"a":[51,68,142],"data-efficient":[52],"ViT":[53],"method":[54],"that":[55,66,90],"uses":[56],"only":[57],"encoder":[59],"standard":[62],"transformer.":[63],"find":[65],"incorporating":[67],"Convolutional":[69],"Neural":[70],"Network":[71],"(CNN)":[72],"feature":[74,116],"extraction":[75],"instead":[76],"original":[79],"patch":[80],"embedding":[81],"and":[82,98,137],"employ":[83],"Sharpness-Aware":[84],"Minimization":[85],"(SAM)":[86],"optimizer":[87],"ensure":[89],"model":[92],"can":[93],"converge":[94],"towards":[95],"flatter":[96],"minima":[97],"yield":[99],"notable":[100],"enhancements.":[101],"Furthermore,":[102],"our":[103,124],"introduction":[104],"span":[107],"mask":[108],"technique,":[109],"which":[110],"masks":[111],"interconnected":[112],"features":[113],"map,":[117],"acts":[118],"as":[119],"an":[120],"effective":[121],"regularizer.":[122],"Empirically,":[123],"approach":[125],"competes":[126],"favorably":[127],"with":[128,153],"traditional":[129],"CNN-based":[130],"small":[133],"like":[135],"IAM":[136],"READ2016.":[138],"Additionally,":[139],"it":[140],"establishes":[141],"new":[143],"benchmark":[144],"LAM":[147],"dataset,":[148],"currently":[149],"largest":[151],"dataset":[152],"19,830":[154],"training":[155],"lines.":[157],"code":[159],"is":[160],"publicly":[161],"available":[162],"at:":[163],"https://github.com/YutingLi0606/HTR-VT.":[164]},"counts_by_year":[],"updated_date":"2025-11-06T06:51:31.235846","created_date":"2025-10-10T00:00:00"}
