{"id":"https://openalex.org/W2607687507","doi":"https://doi.org/10.1109/icpr.2016.7899815","title":"Segmentation of highly unstructured handwritten documents using a neural network technique","display_name":"Segmentation of highly unstructured handwritten documents using a neural network technique","publication_year":2016,"publication_date":"2016-12-01","ids":{"openalex":"https://openalex.org/W2607687507","doi":"https://doi.org/10.1109/icpr.2016.7899815","mag":"2607687507"},"language":"en","primary_location":{"id":"doi:10.1109/icpr.2016.7899815","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2016.7899815","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 23rd International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5072802322","display_name":"Rathin Radhakrishnan Nair","orcid":null},"institutions":[{"id":"https://openalex.org/I63190737","display_name":"University at Buffalo, State University of New York","ror":"https://ror.org/01y64my43","country_code":"US","type":"education","lineage":["https://openalex.org/I63190737"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rathin Radhakrishnan Nair","raw_affiliation_strings":["Department of Computer Science and Engineering, University at Buffalo, Buffalo"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, University at Buffalo, Buffalo","institution_ids":["https://openalex.org/I63190737"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074665893","display_name":"Bharagava Urala Kota","orcid":null},"institutions":[{"id":"https://openalex.org/I63190737","display_name":"University at Buffalo, State University of New York","ror":"https://ror.org/01y64my43","country_code":"US","type":"education","lineage":["https://openalex.org/I63190737"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bharagava Urala Kota","raw_affiliation_strings":["Department of Computer Science and Engineering, University at Buffalo, Buffalo"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, University at Buffalo, Buffalo","institution_ids":["https://openalex.org/I63190737"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022590472","display_name":"Ifeoma Nwogu","orcid":"https://orcid.org/0000-0003-1414-6433"},"institutions":[{"id":"https://openalex.org/I63190737","display_name":"University at Buffalo, State University of New York","ror":"https://ror.org/01y64my43","country_code":"US","type":"education","lineage":["https://openalex.org/I63190737"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ifeoma Nwogu","raw_affiliation_strings":["Department of Computer Science and Engineering, University at Buffalo, Buffalo"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, University at Buffalo, Buffalo","institution_ids":["https://openalex.org/I63190737"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020354604","display_name":"Venu Govindaraju","orcid":"https://orcid.org/0000-0002-5318-7409"},"institutions":[{"id":"https://openalex.org/I63190737","display_name":"University at Buffalo, State University of New York","ror":"https://ror.org/01y64my43","country_code":"US","type":"education","lineage":["https://openalex.org/I63190737"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Venu Govindaraju","raw_affiliation_strings":["Department of Computer Science and Engineering, University at Buffalo, Buffalo"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, University at Buffalo, Buffalo","institution_ids":["https://openalex.org/I63190737"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I63190737"],"apc_list":null,"apc_paid":null,"fwci":0.2013,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.59637044,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"14","issue":null,"first_page":"1291","last_page":"1296"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.9998000264167786,"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":0.9998000264167786,"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/T11309","display_name":"Music and Audio Processing","score":0.9983999729156494,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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":0.9976000189781189,"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":0.8576860427856445},{"id":"https://openalex.org/keywords/optical-character-recognition","display_name":"Optical character recognition","score":0.6579111218452454},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6531921625137329},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.6050422191619873},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.588849663734436},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5306165218353271},{"id":"https://openalex.org/keywords/graphics","display_name":"Graphics","score":0.5183144807815552},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4173491895198822},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.41509103775024414},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38898515701293945},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3657117187976837},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.23282095789909363},{"id":"https://openalex.org/keywords/computer-graphics","display_name":"Computer graphics (images)","score":0.19545236229896545}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8576860427856445},{"id":"https://openalex.org/C546480517","wikidata":"https://www.wikidata.org/wiki/Q167555","display_name":"Optical character recognition","level":3,"score":0.6579111218452454},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6531921625137329},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.6050422191619873},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.588849663734436},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5306165218353271},{"id":"https://openalex.org/C21442007","wikidata":"https://www.wikidata.org/wiki/Q1027879","display_name":"Graphics","level":2,"score":0.5183144807815552},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4173491895198822},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.41509103775024414},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38898515701293945},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3657117187976837},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.23282095789909363},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.19545236229896545}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icpr.2016.7899815","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2016.7899815","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 23rd International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.7300000190734863}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W209269038","https://openalex.org/W1487583988","https://openalex.org/W1880262756","https://openalex.org/W1976507504","https://openalex.org/W1991349032","https://openalex.org/W2003369177","https://openalex.org/W2015432638","https://openalex.org/W2046333072","https://openalex.org/W2047269717","https://openalex.org/W2053370170","https://openalex.org/W2085361026","https://openalex.org/W2110212011","https://openalex.org/W2111099669","https://openalex.org/W2112796928","https://openalex.org/W2119847746","https://openalex.org/W2126925189","https://openalex.org/W2127581753","https://openalex.org/W2129615061","https://openalex.org/W2141053090","https://openalex.org/W2141756865","https://openalex.org/W2151537777","https://openalex.org/W2963542991","https://openalex.org/W3037950864","https://openalex.org/W4213262319","https://openalex.org/W6629368666","https://openalex.org/W6639619044","https://openalex.org/W6696761078"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W2292997772","https://openalex.org/W4321487865","https://openalex.org/W4313906399","https://openalex.org/W2055970094","https://openalex.org/W4391266461","https://openalex.org/W2590798552","https://openalex.org/W4377970376","https://openalex.org/W2811106690","https://openalex.org/W1522196789"],"abstract_inverted_index":{"In":[0],"recent":[1],"years":[2],"there":[3,63],"has":[4],"been":[5],"a":[6,126,143,165,192,213],"growing":[7,195],"interest":[8],"in":[9,106,138,181],"digitizing":[10,30],"the":[11,21,77,104,176,179,187,200,208,221,229,234],"extensive":[12],"amounts":[13],"of":[14,24,28,36,82,103,117,156,178,186,215,228,233],"books":[15],"and":[16,75,87,119,218,244],"documents":[17,158],"that":[18,121,150,171],"existed":[19],"preceding":[20],"widespread":[22],"adoption":[23],"digital":[25],"technologies.":[26],"Many":[27],"these":[29,107],"initiatives":[31],"deal":[32],"with":[33,191],"huge":[34],"collections":[35,86],"handwritten":[37,85,157,182,216],"documents,":[38],"for":[39,59,98],"which":[40],"document":[41],"image":[42],"analysis":[43],"techniques":[44,70,93],"(page":[45],"segmentation,":[46],"keyword-spotting,":[47],"optical":[48],"character":[49],"recognition":[50],"(OCR),":[51],"etc)":[52],"are":[53,189],"not":[54,123],"yet":[55],"as":[56,58],"mature":[57],"printed":[60],"text.":[61],"Thus,":[62,137],"is":[64,151,172,205],"an":[65],"imminent":[66],"need":[67],"to":[68,71,134,153,174,197],"develop":[69],"understand,":[72],"archive,":[73],"index":[74],"search":[76],"manuscripts.":[78,183],"The":[79,184,203],"antiquated":[80],"approach":[81],"manually":[83],"transcribing":[84],"then":[88],"using":[89],"standard":[90],"text":[91],"retrieval":[92],"can":[94],"be":[95],"very":[96],"expensive":[97],"large":[99],"collections.":[100],"But":[101],"many":[102],"manuscripts":[105],"collections,":[108],"unlike":[109],"machine-printed":[110],"texts,":[111],"contain":[112],"unstructured":[113],"information,":[114],"cluttered":[115],"group":[116],"texts":[118],"graphics":[120],"do":[122],"necessarily":[124],"follow":[125],"pre-specified":[127],"format,":[128],"thus":[129],"making":[130],"it":[131],"quite":[132],"challenging":[133],"automatically":[135],"process.":[136],"this":[139],"paper":[140],"we":[141],"present":[142,238],"convolutional":[144],"neural":[145],"network":[146,170,188],"(CNN)":[147],"based":[148,169],"implementation":[149,204],"used":[152],"segment":[154],"pages":[155,180],"into":[159],"their":[160],"constituent":[161],"sections.":[162],"We":[163,237],"showcase":[164],"multiscale":[166],"sliding":[167],"window":[168],"trained":[173],"predict":[175],"sections":[177],"results":[185,241],"post-processed":[190],"novel":[193],"region":[194],"technique":[196],"further":[198],"improve":[199],"segmentation":[201,240],"results.":[202],"applied":[206],"on":[207],"Marianne":[209,224],"Moore":[210,225],"archival":[211],"collection,":[212],"body":[214],"notes":[217],"memos":[219],"by":[220],"renowned":[222],"author":[223],"(1887-1972),":[226],"one":[227],"foremost":[230],"modernist":[231],"poets":[232],"early":[235],"twentieth-century.":[236],"our":[239],"both":[242],"quantitatively":[243],"qualitatively.":[245]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}