{"id":"https://openalex.org/W4414118033","doi":"https://doi.org/10.1109/fuzz62266.2025.11152168","title":"Minimizing Protoform Redundancy to Enhance Linguistic Summaries in Object Detection","display_name":"Minimizing Protoform Redundancy to Enhance Linguistic Summaries in Object Detection","publication_year":2025,"publication_date":"2025-07-06","ids":{"openalex":"https://openalex.org/W4414118033","doi":"https://doi.org/10.1109/fuzz62266.2025.11152168"},"language":"en","primary_location":{"id":"doi:10.1109/fuzz62266.2025.11152168","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fuzz62266.2025.11152168","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Fuzzy Systems (FUZZ)","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/A5074167868","display_name":"Brendan Alvey","orcid":null},"institutions":[{"id":"https://openalex.org/I76835614","display_name":"University of Missouri","ror":"https://ror.org/02ymw8z06","country_code":"US","type":"education","lineage":["https://openalex.org/I76835614"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Brendan Alvey","raw_affiliation_strings":["University of Missouri,Dept. of EECS,Columbia,MO,USA"],"affiliations":[{"raw_affiliation_string":"University of Missouri,Dept. of EECS,Columbia,MO,USA","institution_ids":["https://openalex.org/I76835614"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076164452","display_name":"Derek T. Anderson","orcid":"https://orcid.org/0000-0003-4909-029X"},"institutions":[{"id":"https://openalex.org/I76835614","display_name":"University of Missouri","ror":"https://ror.org/02ymw8z06","country_code":"US","type":"education","lineage":["https://openalex.org/I76835614"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Derek Anderson","raw_affiliation_strings":["University of Missouri,Dept. of EECS,Columbia,MO,USA"],"affiliations":[{"raw_affiliation_string":"University of Missouri,Dept. of EECS,Columbia,MO,USA","institution_ids":["https://openalex.org/I76835614"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018303984","display_name":"James M. Keller","orcid":"https://orcid.org/0000-0002-0306-7142"},"institutions":[{"id":"https://openalex.org/I76835614","display_name":"University of Missouri","ror":"https://ror.org/02ymw8z06","country_code":"US","type":"education","lineage":["https://openalex.org/I76835614"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"James Keller","raw_affiliation_strings":["University of Missouri,Dept. of EECS,Columbia,MO,USA"],"affiliations":[{"raw_affiliation_string":"University of Missouri,Dept. of EECS,Columbia,MO,USA","institution_ids":["https://openalex.org/I76835614"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5074167868"],"corresponding_institution_ids":["https://openalex.org/I76835614"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.2504787,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","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"}},"topics":[{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9973000288009644,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9968000054359436,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.6661999821662903},{"id":"https://openalex.org/keywords/parsing","display_name":"Parsing","score":0.5037000179290771},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.44940000772476196},{"id":"https://openalex.org/keywords/raw-data","display_name":"Raw data","score":0.4302999973297119},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.4194999933242798},{"id":"https://openalex.org/keywords/trustworthiness","display_name":"Trustworthiness","score":0.4059999883174896},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4041999876499176},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.37229999899864197},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.35920000076293945}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7986000180244446},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.6661999821662903},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5403000116348267},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5062999725341797},{"id":"https://openalex.org/C186644900","wikidata":"https://www.wikidata.org/wiki/Q194152","display_name":"Parsing","level":2,"score":0.5037000179290771},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.44940000772476196},{"id":"https://openalex.org/C132964779","wikidata":"https://www.wikidata.org/wiki/Q2110223","display_name":"Raw data","level":2,"score":0.4302999973297119},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.4194999933242798},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4115000069141388},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.40619999170303345},{"id":"https://openalex.org/C153701036","wikidata":"https://www.wikidata.org/wiki/Q659974","display_name":"Trustworthiness","level":2,"score":0.4059999883174896},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4041999876499176},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.37229999899864197},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.35920000076293945},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.34869998693466187},{"id":"https://openalex.org/C2780586970","wikidata":"https://www.wikidata.org/wiki/Q1357284","display_name":"Popularity","level":2,"score":0.33880001306533813},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.30970001220703125},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.29820001125335693},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.2921999990940094},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.28360000252723694},{"id":"https://openalex.org/C7545210","wikidata":"https://www.wikidata.org/wiki/Q838123","display_name":"Data redundancy","level":2,"score":0.2827000021934509},{"id":"https://openalex.org/C2983685735","wikidata":"https://www.wikidata.org/wiki/Q5227355","display_name":"Data source","level":2,"score":0.2712000012397766},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.26840001344680786},{"id":"https://openalex.org/C32587265","wikidata":"https://www.wikidata.org/wiki/Q1182260","display_name":"Data deduplication","level":2,"score":0.26660001277923584},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2605000138282776},{"id":"https://openalex.org/C53893814","wikidata":"https://www.wikidata.org/wiki/Q7378909","display_name":"Rule-based machine translation","level":2,"score":0.2583000063896179},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.2547000050544739},{"id":"https://openalex.org/C74197172","wikidata":"https://www.wikidata.org/wiki/Q1195339","display_name":"Directed acyclic graph","level":2,"score":0.2524000108242035}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/fuzz62266.2025.11152168","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fuzz62266.2025.11152168","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Fuzzy Systems (FUZZ)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W996183064","https://openalex.org/W1861492603","https://openalex.org/W2012474584","https://openalex.org/W2082717534","https://openalex.org/W2167583851","https://openalex.org/W2544536995","https://openalex.org/W2549139847","https://openalex.org/W2989604896","https://openalex.org/W3081984940","https://openalex.org/W3134642945","https://openalex.org/W3191339631","https://openalex.org/W4221146106","https://openalex.org/W4385292963","https://openalex.org/W4385485053","https://openalex.org/W4386071535","https://openalex.org/W4387725212","https://openalex.org/W4388129790","https://openalex.org/W4389520124","https://openalex.org/W4400342223","https://openalex.org/W4400702658","https://openalex.org/W4401042993","https://openalex.org/W4401329116","https://openalex.org/W4405618561","https://openalex.org/W4414014501"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W3204019825"],"abstract_inverted_index":{"Large":[0],"language":[1],"models":[2],"(LLMs)":[3],"have":[4],"gained":[5],"widespread":[6],"popularity":[7],"because":[8],"of":[9,24,65,108,114,131,152,164],"their":[10,76],"remarkable":[11],"capabilities.":[12],"However,":[13],"they":[14],"cannot":[15],"yet":[16],"be":[17,40],"relied":[18],"upon":[19],"to":[20,71,134],"process":[21],"large":[22,63],"amounts":[23],"raw":[25],"data":[26,44,170,178],"and":[27,53,73,117,171],"consistently":[28],"produce":[29],"trustworthy":[30],"results":[31],"while":[32],"preserving":[33],"privacy.":[34],"In":[35],"contrast,":[36],"linguistic":[37,48,143],"summaries":[38,59],"can":[39],"generated":[41,179],"from":[42],"these":[43,89],"sources":[45],"using":[46,180],"fuzzy":[47],"proforms":[49],"ranked":[50],"by":[51],"accuracy":[52],"other":[54],"relevant":[55],"metrics.":[56],"Unfortunately,":[57],"such":[58,148],"often":[60],"yield":[61],"a":[62,85,93,124,172],"number":[64],"redundant":[66],"statements,":[67,90],"making":[68],"them":[69],"difficult":[70],"parse":[72],"thus":[74],"reducing":[75],"overall":[77],"effectiveness.":[78],"To":[79,127],"address":[80],"this":[81,132],"issue,":[82],"we":[83,137],"introduce":[84],"method":[86],"for":[87,110,141],"processing":[88],"represented":[91],"as":[92,149],"directed":[94],"acyclic":[95],"graph":[96],"that":[97],"significantly":[98],"reduces":[99],"redundancy":[100],"in":[101],"the":[102,111,129,162,181],"resulting":[103],"summaries.":[104],"We":[105,160],"take":[106],"advantage":[107],"LLMs":[109],"narrow":[112],"task":[113],"further":[115],"enhancing":[116],"summarizing":[118],"our":[119,165],"already":[120],"reduced":[121],"protoforms,":[122],"presenting":[123],"combined":[125],"approach.":[126],"facilitate":[128],"application":[130],"technique":[133],"object":[135],"detection,":[136],"also":[138],"propose":[139],"methods":[140],"computing":[142],"qualities":[144],"over":[145],"heterogeneous":[146],"sets,":[147],"different":[150],"types":[151],"declarations":[153],"(e.g.,":[154],"false":[155],"alarms":[156],"vs.":[157],"missed":[158],"targets).":[159],"demonstrate":[161],"effectiveness":[163],"approach":[166],"on":[167,177],"both":[168],"synthetic":[169],"real":[173],"person-detection":[174],"model":[175],"tested":[176],"Unreal":[182],"Engine.":[183]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-10-10T00:00:00"}