{"id":"https://openalex.org/W2179703327","doi":"https://doi.org/10.1109/fuzz-ieee.2015.7338108","title":"An improved BOW approach using fuzzy feature encoding and visual-word weighting","display_name":"An improved BOW approach using fuzzy feature encoding and visual-word weighting","publication_year":2015,"publication_date":"2015-08-01","ids":{"openalex":"https://openalex.org/W2179703327","doi":"https://doi.org/10.1109/fuzz-ieee.2015.7338108","mag":"2179703327"},"language":"en","primary_location":{"id":"doi:10.1109/fuzz-ieee.2015.7338108","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fuzz-ieee.2015.7338108","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://hdl.handle.net/11511/55629","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5010414147","display_name":"Umit Lutfu Altintakan","orcid":"https://orcid.org/0000-0002-6056-8736"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Umit L. Altintakan","raw_affiliation_strings":["Independent Researcher NATO E-3A Component, Geilenkirchen, Germany"],"affiliations":[{"raw_affiliation_string":"Independent Researcher NATO E-3A Component, Geilenkirchen, Germany","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020101419","display_name":"Adnan Yaz\u0131c\u0131","orcid":"https://orcid.org/0000-0001-9404-9494"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Adnan Yazici","raw_affiliation_strings":["Independent Researcher NATO E-3A Component, Geilenkirchen, Germany"],"affiliations":[{"raw_affiliation_string":"Independent Researcher NATO E-3A Component, Geilenkirchen, Germany","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5010414147"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.5615,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.75354229,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"25","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":1.0,"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"}},{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9997000098228455,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9941999912261963,"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/codebook","display_name":"Codebook","score":0.8250218629837036},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.728704571723938},{"id":"https://openalex.org/keywords/visual-word","display_name":"Visual Word","score":0.7247511744499207},{"id":"https://openalex.org/keywords/bag-of-words-model","display_name":"Bag-of-words model","score":0.7131591439247131},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7020094394683838},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.6721121072769165},{"id":"https://openalex.org/keywords/bag-of-words-model-in-computer-vision","display_name":"Bag-of-words model in computer vision","score":0.6676398515701294},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6601261496543884},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.6274356842041016},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6251641511917114},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.607941210269928},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.529185950756073},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.4916155934333801},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.47909215092658997},{"id":"https://openalex.org/keywords/fuzzy-set","display_name":"Fuzzy set","score":0.4709041118621826},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.42948591709136963},{"id":"https://openalex.org/keywords/image-retrieval","display_name":"Image retrieval","score":0.4223971366882324},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.40155258774757385},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.17535856366157532}],"concepts":[{"id":"https://openalex.org/C127759330","wikidata":"https://www.wikidata.org/wiki/Q637416","display_name":"Codebook","level":2,"score":0.8250218629837036},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.728704571723938},{"id":"https://openalex.org/C189391414","wikidata":"https://www.wikidata.org/wiki/Q7936579","display_name":"Visual Word","level":4,"score":0.7247511744499207},{"id":"https://openalex.org/C13672336","wikidata":"https://www.wikidata.org/wiki/Q3460803","display_name":"Bag-of-words model","level":2,"score":0.7131591439247131},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7020094394683838},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.6721121072769165},{"id":"https://openalex.org/C167611913","wikidata":"https://www.wikidata.org/wiki/Q6884747","display_name":"Bag-of-words model in computer vision","level":5,"score":0.6676398515701294},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6601261496543884},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.6274356842041016},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6251641511917114},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.607941210269928},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.529185950756073},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.4916155934333801},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.47909215092658997},{"id":"https://openalex.org/C42011625","wikidata":"https://www.wikidata.org/wiki/Q1055058","display_name":"Fuzzy set","level":3,"score":0.4709041118621826},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.42948591709136963},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.4223971366882324},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.40155258774757385},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17535856366157532},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"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/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/fuzz-ieee.2015.7338108","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fuzz-ieee.2015.7338108","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)","raw_type":"proceedings-article"},{"id":"pmh:oai:open.metu.edu.tr:11511/55629","is_oa":true,"landing_page_url":"https://hdl.handle.net/11511/55629","pdf_url":null,"source":{"id":"https://openalex.org/S4306402495","display_name":"OpenMETU (Middle East Technical University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I201799495","host_organization_name":"Middle East Technical University","host_organization_lineage":["https://openalex.org/I201799495"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference Paper"}],"best_oa_location":{"id":"pmh:oai:open.metu.edu.tr:11511/55629","is_oa":true,"landing_page_url":"https://hdl.handle.net/11511/55629","pdf_url":null,"source":{"id":"https://openalex.org/S4306402495","display_name":"OpenMETU (Middle East Technical University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I201799495","host_organization_name":"Middle East Technical University","host_organization_lineage":["https://openalex.org/I201799495"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference Paper"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1905930958","https://openalex.org/W1976921161","https://openalex.org/W1988920861","https://openalex.org/W1995034545","https://openalex.org/W2000323888","https://openalex.org/W2022020940","https://openalex.org/W2031489346","https://openalex.org/W2033235641","https://openalex.org/W2066941820","https://openalex.org/W2081655032","https://openalex.org/W2098407371","https://openalex.org/W2119605622","https://openalex.org/W2123745357","https://openalex.org/W2131846894","https://openalex.org/W2144270470","https://openalex.org/W2148809503","https://openalex.org/W2148809531","https://openalex.org/W2150692003","https://openalex.org/W2151103935","https://openalex.org/W2155490028","https://openalex.org/W6647613022","https://openalex.org/W6678853083"],"related_works":["https://openalex.org/W1615295117","https://openalex.org/W2158102958","https://openalex.org/W2035094092","https://openalex.org/W2277784908","https://openalex.org/W2947282851","https://openalex.org/W2045213079","https://openalex.org/W2938717424","https://openalex.org/W3043037362","https://openalex.org/W2179703327","https://openalex.org/W2587721114"],"abstract_inverted_index":{"The":[0],"bag-of-words":[1],"(BOW)":[2],"has":[3,20,35],"become":[4],"a":[5,43,91],"popular":[6],"image":[7,60,70,96,100,106,119],"representation":[8],"model":[9,19],"with":[10,53],"successful":[11],"implementations":[12],"in":[13,23,33,80,116],"visual":[14],"analysis.":[15],"Although":[16],"the":[17,26,29,50,54,63,74,81,85,113],"original":[18],"been":[21,37],"improved":[22],"several":[24],"ways,":[25],"utilization":[27],"of":[28,59],"Fuzzy":[30],"Set":[31],"Theory":[32],"BOW":[34,114],"not":[36],"investigated":[38],"thoroughly.":[39],"This":[40],"paper":[41],"presents":[42],"fuzzy":[44],"feature":[45,71],"encoding":[46,66],"approach":[47],"to":[48,62,72,83],"address":[49],"problems":[51],"associated":[52],"hard":[55],"and":[56,76],"soft":[57],"assignments":[58],"features":[61],"visual-words.":[64],"Our":[65],"method":[67],"assigns":[68],"each":[69],"only":[73],"first":[75],"second":[77],"closest":[78],"words":[79],"codebook":[82],"overcome":[84],"word-uncertainty":[86],"problem.":[87],"Moreover,":[88],"we":[89],"introduce":[90],"new":[92],"word-weighting":[93],"scheme":[94],"for":[95],"categories":[97],"based":[98,118],"on":[99,104],"histograms.":[101],"Experiments":[102],"conducted":[103],"some":[105],"datasets":[107],"show":[108],"that":[109],"both":[110],"methods":[111],"increase":[112],"performance":[115],"content":[117],"retrieval.":[120]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}