{"id":"https://openalex.org/W2993187506","doi":"https://doi.org/10.1109/ispacs.2018.8923153","title":"An Extraction Method of Handwritten Characters on Printed Documents by Maxout Filter Networks","display_name":"An Extraction Method of Handwritten Characters on Printed Documents by Maxout Filter Networks","publication_year":2018,"publication_date":"2018-11-01","ids":{"openalex":"https://openalex.org/W2993187506","doi":"https://doi.org/10.1109/ispacs.2018.8923153","mag":"2993187506"},"language":"en","primary_location":{"id":"doi:10.1109/ispacs.2018.8923153","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ispacs.2018.8923153","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)","raw_type":"proceedings-article"},"type":"article","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/A5026211563","display_name":"Kiyoaki Itoi","orcid":null},"institutions":[{"id":"https://openalex.org/I8488066","display_name":"Chiba Institute of Technology","ror":"https://ror.org/00qwnam72","country_code":"JP","type":"education","lineage":["https://openalex.org/I8488066"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Kiyoaki Itoi","raw_affiliation_strings":["Faculty of Engineering, Chiba Institute of Technology, Narashino-shi, Japan"],"affiliations":[{"raw_affiliation_string":"Faculty of Engineering, Chiba Institute of Technology, Narashino-shi, Japan","institution_ids":["https://openalex.org/I8488066"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072730094","display_name":"Makoto Nakashizuka","orcid":null},"institutions":[{"id":"https://openalex.org/I8488066","display_name":"Chiba Institute of Technology","ror":"https://ror.org/00qwnam72","country_code":"JP","type":"education","lineage":["https://openalex.org/I8488066"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Makoto Nakashizuka","raw_affiliation_strings":["Faculty of Engineering, Chiba Institute of Technology, Narashino-shi, Japan"],"affiliations":[{"raw_affiliation_string":"Faculty of Engineering, Chiba Institute of Technology, Narashino-shi, Japan","institution_ids":["https://openalex.org/I8488066"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5026211563"],"corresponding_institution_ids":["https://openalex.org/I8488066"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.25139802,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"1","issue":null,"first_page":"504","last_page":"509"},"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/T12707","display_name":"Vehicle License Plate Recognition","score":0.9965000152587891,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T14339","display_name":"Image Processing and 3D Reconstruction","score":0.9947999715805054,"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":0.7992644309997559},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6696893572807312},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.6010944843292236},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.5429465770721436},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.48450157046318054},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4730343520641327},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.4120975732803345},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.4039511978626251},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.2831967771053314},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09157741069793701}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7992644309997559},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6696893572807312},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.6010944843292236},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.5429465770721436},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.48450157046318054},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4730343520641327},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.4120975732803345},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4039511978626251},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2831967771053314},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09157741069793701},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ispacs.2018.8923153","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ispacs.2018.8923153","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","score":0.8999999761581421,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W60978252","https://openalex.org/W2065632200","https://openalex.org/W2114926173","https://openalex.org/W2140554723","https://openalex.org/W2146502635","https://openalex.org/W2194775991","https://openalex.org/W2294059674","https://openalex.org/W2508457857","https://openalex.org/W2753772327","https://openalex.org/W2765793594","https://openalex.org/W4230855036","https://openalex.org/W6680582415","https://openalex.org/W6681435938","https://openalex.org/W6696761078"],"related_works":["https://openalex.org/W2601157893","https://openalex.org/W2131735617","https://openalex.org/W2373006798","https://openalex.org/W2056912418","https://openalex.org/W2123759770","https://openalex.org/W2033213769","https://openalex.org/W2811390910","https://openalex.org/W4312376745","https://openalex.org/W2082269393","https://openalex.org/W2043960970"],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"an":[3,77],"extraction":[4,18,62,75,95,171],"method":[5],"of":[6,19,37,63,79,89,92,96,102,119,138,163,172,184,194],"handwritten":[7,20,29,65,98,174],"characters":[8,21,66],"written":[9],"on":[10],"printed":[11,26,112],"documents":[12],"using":[13],"maxout":[14,47,54,71,104],"filter":[15,72],"networks.":[16],"The":[17,70,182],"from":[22,67,176],"document":[23,39,178],"images,":[24],"e.g.":[25],"text":[27],"with":[28,52,134,187],"annotation,":[30],"plays":[31],"important":[32],"roles":[33],"in":[34],"the":[35,38,46,53,64,68,74,80,87,97,100,103,111,117,120,136,144,150,157,161,164,168,170,173,177,185,188,192,195],"field":[36],"analysis":[40],"and":[41,59,160],"recognition.":[42],"In":[43,122,167],"this":[44],"paper,":[45],"filters":[48,105],"that":[49,131,148],"are":[50,57,106],"composed":[51],"activation":[55],"functions":[56],"trained":[58,107],"applied":[60],"to":[61,108,124,155],"documents.":[69],"for":[73],"is":[76,141,153,180],"extension":[78],"morphological":[81],"closing":[82],"filter,":[83],"which":[84,114],"can":[85],"eliminate":[86,109],"valleys":[88,118],"intensity":[90],"surface":[91],"images.":[93,166],"For":[94],"characters,":[99,113],"parameters":[101,133],"only":[110],"appear":[115],"as":[116],"intensity.":[121],"order":[123],"handle":[125],"multiple":[126],"writers,":[127],"a":[128],"batch":[129],"learning":[130,158],"trains":[132],"averaging":[135],"errors":[137],"each":[139],"writer":[140],"introduced.":[142],"Moreover,":[143],"novel":[145],"network":[146,190],"configuration":[147],"has":[149],"skipping":[151],"path":[152],"introduced":[154],"improve":[156],"rate":[159],"quality":[162],"extracted":[165],"experiments,":[169],"annotation":[175],"images":[179],"demonstrated.":[181],"results":[183],"comparison":[186],"conventional":[189],"shows":[191],"advantage":[193],"proposed":[196],"network.":[197]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
