{"id":"https://openalex.org/W2014564469","doi":"https://doi.org/10.1109/iccict.2015.7045738","title":"A fuzzy based classification scheme for unconstrained handwritten Devanagari character recognition","display_name":"A fuzzy based classification scheme for unconstrained handwritten Devanagari character recognition","publication_year":2015,"publication_date":"2015-01-01","ids":{"openalex":"https://openalex.org/W2014564469","doi":"https://doi.org/10.1109/iccict.2015.7045738","mag":"2014564469"},"language":"en","primary_location":{"id":"doi:10.1109/iccict.2015.7045738","doi":"https://doi.org/10.1109/iccict.2015.7045738","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccict.2015.7045738","pdf_url":null,"source":{"id":"https://openalex.org/S4306423357","display_name":"International Conference on Communication, Information & Computing Technology","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 International Conference on Communication, Information &amp; Computing Technology (ICCICT)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"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/A5066145195","display_name":"Sushama Shelke","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sushama Shelke","raw_affiliation_strings":["Electronics and Telecommunication, NBN Sinhgad School of Engineering, Pune, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Electronics and Telecommunication, NBN Sinhgad School of Engineering, Pune, India","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5022065577","display_name":"Shaila Dinkar Apte","orcid":"https://orcid.org/0000-0001-6703-7324","observed_orcids":["https://orcid.org/0000-0001-6703-7324"]},"institutions":[{"id":"https://openalex.org/I4405285498","display_name":"JSPM's Rajarshi Shahu College of Engineering","ror":"https://ror.org/05jnzdx13","country_code":"IN","type":"education","lineage":["https://openalex.org/I4405285498"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Shaila Apte","raw_affiliation_strings":["Electronics and Telecommunication, Rajarshi Shahu College of Engineering, Pune, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Electronics and Telecommunication, Rajarshi Shahu College of Engineering, Pune, India","institution_ids":["https://openalex.org/I4405285498"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.3356,"has_fulltext":false,"cited_by_count":35,"citation_normalized_percentile":{"value":0.8976444,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.9994999766349792,"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":0.9994999766349792,"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":0.00019999999494757503,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.0,"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/handwritten-character-recognition","display_name":"handwritten character recognition","score":0.9710000157356262},{"id":"https://openalex.org/keywords/unconstrained-handwriting","display_name":"unconstrained handwriting","score":0.8379999995231628},{"id":"https://openalex.org/keywords/fuzzy-inference-system","display_name":"fuzzy inference system","score":0.9589999914169312},{"id":"https://openalex.org/keywords/multi-stage-classification","display_name":"multi-stage classification","score":0.9319999814033508},{"id":"https://openalex.org/keywords/structural-parameters","display_name":"structural parameters","score":0.8100000023841858},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"feature extraction","score":0.9800000190734863},{"id":"https://openalex.org/keywords/feedforward-neural-networks","display_name":"feedforward neural networks","score":0.8489999771118164},{"id":"https://openalex.org/keywords/script-identification","display_name":"script recognition","score":0.4339999854564667}],"concepts":[{"id":"https://openalex.org/C2780144916","wikidata":"https://www.wikidata.org/wiki/Q38592","display_name":"Devanagari","level":4,"score":0.9298677444458008},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7093035578727722},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.697279691696167},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6962534785270691},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5265703201293945},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.5066903233528137},{"id":"https://openalex.org/C94124525","wikidata":"https://www.wikidata.org/wiki/Q912550","display_name":"Categorization","level":2,"score":0.5032340884208679},{"id":"https://openalex.org/C2780861071","wikidata":"https://www.wikidata.org/wiki/Q1062934","display_name":"Character (mathematics)","level":2,"score":0.4484262764453888},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.44739121198654175},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.4442819654941559},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.44355523586273193},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4153531491756439},{"id":"https://openalex.org/C2987247673","wikidata":"https://www.wikidata.org/wiki/Q167555","display_name":"Character recognition","level":3,"score":0.3093997836112976},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13288411498069763},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccict.2015.7045738","doi":"https://doi.org/10.1109/iccict.2015.7045738","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccict.2015.7045738","pdf_url":null,"source":{"id":"https://openalex.org/S4306423357","display_name":"International Conference on Communication, Information & Computing Technology","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 International Conference on Communication, Information &amp; Computing Technology (ICCICT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1539378127","https://openalex.org/W1604786357","https://openalex.org/W1730152048","https://openalex.org/W1825077972","https://openalex.org/W1977218226","https://openalex.org/W1988898746","https://openalex.org/W1996709837","https://openalex.org/W2017787659","https://openalex.org/W2039098241","https://openalex.org/W2044943596","https://openalex.org/W2086964741","https://openalex.org/W2093402801","https://openalex.org/W2116128970","https://openalex.org/W2138453757","https://openalex.org/W2155947133","https://openalex.org/W2160545881","https://openalex.org/W2952068244","https://openalex.org/W6638473186"],"related_works":["https://openalex.org/W7096917571","https://openalex.org/W59953257","https://openalex.org/W2588083334","https://openalex.org/W2062505792","https://openalex.org/W2166494748","https://openalex.org/W2145345986","https://openalex.org/W2952068244","https://openalex.org/W3145839214","https://openalex.org/W4391901995","https://openalex.org/W2138453757"],"abstract_inverted_index":{"The":[0,36,44,53,76,85,95,106],"large":[1],"data":[2],"set":[3],"and":[4,19,68],"similar":[5],"structural":[6,74],"features":[7],"of":[8,31],"the":[9,29,48,80,91,111],"characters":[10,49,87],"in":[11],"Devanagari":[12,34],"script":[13],"demand":[14],"a":[15,25],"highly":[16],"efficient":[17],"classification":[18,42,45,54,81],"recognition":[20,30,107],"system.":[21],"This":[22],"paper":[23],"presents":[24],"novel":[26],"approach":[27],"for":[28,103],"unconstrained":[32],"handwritten":[33],"characters.":[35],"system":[37,67,78],"is":[38,55,62,71,114],"based":[39,63,72],"on":[40,64,73],"multi-stage":[41],"scheme.":[43],"stages":[46],"categorize":[47],"into":[50],"smaller":[51],"groups.":[52],"done":[56],"using":[57],"two":[58],"stages,":[59],"first":[60],"stage":[61,70,97],"fuzzy":[65,77],"inference":[66],"second":[69],"parameters.":[75],"improves":[79],"over":[82],"crisp":[83],"classification.":[84],"classified":[86],"are":[88],"passed":[89],"to":[90],"feature":[92],"extraction":[93],"stage.":[94],"final":[96],"implements":[98],"feed":[99],"forward":[100],"neural":[101],"network":[102],"character":[104],"recognition.":[105],"accuracy":[108],"achieved":[109],"by":[110],"proposed":[112],"method":[113],"96.95%.":[115]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":4}],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2016-06-24T00:00:00"}
