{"id":"https://openalex.org/W2139730977","doi":"https://doi.org/10.1142/s0218001497000421","title":"Empirical Design of a Multi-Classifier Thresholding/Control Strategy for Recognition of Handwritten Street Names","display_name":"Empirical Design of a Multi-Classifier Thresholding/Control Strategy for Recognition of Handwritten Street Names","publication_year":1997,"publication_date":"1997-09-01","ids":{"openalex":"https://openalex.org/W2139730977","doi":"https://doi.org/10.1142/s0218001497000421","mag":"2139730977"},"language":"en","primary_location":{"id":"doi:10.1142/s0218001497000421","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218001497000421","pdf_url":null,"source":{"id":"https://openalex.org/S41486457","display_name":"International Journal of Pattern Recognition and Artificial Intelligence","issn_l":"0218-0014","issn":["0218-0014","1793-6381"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Pattern Recognition and Artificial Intelligence","raw_type":"journal-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/A5000159830","display_name":"Sriganesh Madhvanath","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":true,"raw_author_name":"S. Madhvanath","raw_affiliation_strings":["Center of Excellence for Document Analysis and Recognition (CEDAR), State University of New York at Buffalo, New York"],"affiliations":[{"raw_affiliation_string":"Center of Excellence for Document Analysis and Recognition (CEDAR), State University of New York at Buffalo, New York","institution_ids":["https://openalex.org/I63190737"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034562840","display_name":"E. M. Kleinberg","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":"E. Kleinberg","raw_affiliation_strings":["Center of Excellence for Document Analysis and Recognition (CEDAR), State University of New York at Buffalo, New York"],"affiliations":[{"raw_affiliation_string":"Center of Excellence for Document Analysis and Recognition (CEDAR), State University of New York at Buffalo, New York","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":"V. Govindaraju","raw_affiliation_strings":["Center of Excellence for Document Analysis and Recognition (CEDAR), State University of New York at Buffalo, New York"],"affiliations":[{"raw_affiliation_string":"Center of Excellence for Document Analysis and Recognition (CEDAR), State University of New York at Buffalo, New York","institution_ids":["https://openalex.org/I63190737"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5000159830"],"corresponding_institution_ids":["https://openalex.org/I63190737"],"apc_list":null,"apc_paid":null,"fwci":2.3076,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.89716024,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"11","issue":"06","first_page":"933","last_page":"946"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.9994000196456909,"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":0.9994000196456909,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9937999844551086,"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"}},{"id":"https://openalex.org/T12707","display_name":"Vehicle License Plate Recognition","score":0.9814000129699707,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8121950030326843},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6517943739891052},{"id":"https://openalex.org/keywords/lexicon","display_name":"Lexicon","score":0.6483173966407776},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6406079530715942},{"id":"https://openalex.org/keywords/thresholding","display_name":"Thresholding","score":0.6039965748786926},{"id":"https://openalex.org/keywords/word-error-rate","display_name":"Word error rate","score":0.49002254009246826},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4488155245780945},{"id":"https://openalex.org/keywords/intelligent-word-recognition","display_name":"Intelligent word recognition","score":0.4187651574611664},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.34012314677238464},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3292720913887024},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32293665409088135},{"id":"https://openalex.org/keywords/character-recognition","display_name":"Character recognition","score":0.2825264632701874},{"id":"https://openalex.org/keywords/intelligent-character-recognition","display_name":"Intelligent character recognition","score":0.23038432002067566}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8121950030326843},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6517943739891052},{"id":"https://openalex.org/C2778121359","wikidata":"https://www.wikidata.org/wiki/Q8096","display_name":"Lexicon","level":2,"score":0.6483173966407776},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6406079530715942},{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.6039965748786926},{"id":"https://openalex.org/C40969351","wikidata":"https://www.wikidata.org/wiki/Q3516228","display_name":"Word error rate","level":2,"score":0.49002254009246826},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4488155245780945},{"id":"https://openalex.org/C17649283","wikidata":"https://www.wikidata.org/wiki/Q6044162","display_name":"Intelligent word recognition","level":5,"score":0.4187651574611664},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.34012314677238464},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3292720913887024},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32293665409088135},{"id":"https://openalex.org/C2987247673","wikidata":"https://www.wikidata.org/wiki/Q167555","display_name":"Character recognition","level":3,"score":0.2825264632701874},{"id":"https://openalex.org/C44868376","wikidata":"https://www.wikidata.org/wiki/Q3099089","display_name":"Intelligent character recognition","level":4,"score":0.23038432002067566},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1142/s0218001497000421","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218001497000421","pdf_url":null,"source":{"id":"https://openalex.org/S41486457","display_name":"International Journal of Pattern Recognition and Artificial Intelligence","issn_l":"0218-0014","issn":["0218-0014","1793-6381"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Pattern Recognition and Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.550000011920929,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2953058328","https://openalex.org/W2140536630","https://openalex.org/W2391730868","https://openalex.org/W1542224353","https://openalex.org/W2759814045","https://openalex.org/W2118055728","https://openalex.org/W2030443174","https://openalex.org/W2143713599","https://openalex.org/W2136016133","https://openalex.org/W2140685796"],"abstract_inverted_index":{"A":[0,19],"central":[1],"task":[2,57],"in":[3,75,82,121],"the":[4,12,16,45,62,67,83,94],"interpretation":[5,110],"of":[6,15,21,31,66,96,105,115],"handwritten":[7,53,108],"US":[8],"postal":[9,32],"addresses":[10],"is":[11,58],"off-line":[13,52],"recognition":[14,55,127],"street":[17,23],"name.":[18],"lexicon":[20,146],"candidate":[22],"names":[24],"may":[25],"be":[26],"extracted":[27],"from":[28,73],"a":[29,97,106,122],"database":[30],"delivery":[33],"points":[34],"(DPF)":[35],"by":[36,61],"first":[37],"locating":[38],"and":[39,48,69,79,128,140,145,161],"recognizing":[40],"numeric":[41,77],"fields":[42,78],"such":[43],"as":[44,151,153],"ZIP":[46],"code":[47],"strewet":[49],"number.":[50],"The":[51,113,135,155],"word":[54,117],"(HWR)":[56],"made":[59],"difficult":[60],"unconstrained,":[63],"omni-scriptor":[64],"nature":[65],"input,":[68],"incomplete":[70],"lexicons":[71],"resulting":[72],"errors":[74],"processing":[76],"intrinsic":[80],"deficiencies":[81],"DPF.":[84],"In":[85],"this":[86],"paper,":[87],"we":[88],"describe":[89],"an":[90],"empirical":[91],"approach":[92],"to":[93,125],"design":[95,136],"multi-classifier":[98],"HWR":[99],"Thresholding/Control":[100],"module":[101],"which":[102],"forms":[103],"part":[104],"real-time":[107,133],"address":[109],"(HWAI)":[111],"system.":[112],"decisions":[114],"two":[116],"classifiers":[118],"are":[119],"combined":[120],"hierarchical":[123],"manner":[124],"improve":[126],"error-rejection":[129],"performance,":[130],"while":[131],"meeting":[132],"requirements.":[134],"employs":[137],"logistic":[138],"regression":[139],"agreement":[141],"for":[142,148,163],"evidence":[143],"combination,":[144],"reduction":[147],"improved":[149],"throughput":[150],"well":[152],"performance.":[154],"paper":[156],"concludes":[157],"with":[158],"experimental":[159],"results":[160],"directions":[162],"future":[164],"research.":[165]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}