{"id":"https://openalex.org/W2607930008","doi":"https://doi.org/10.1109/icpr.2016.7899768","title":"Improving classifier fusion via Pool Adjacent Violators normalization","display_name":"Improving classifier fusion via Pool Adjacent Violators normalization","publication_year":2016,"publication_date":"2016-12-01","ids":{"openalex":"https://openalex.org/W2607930008","doi":"https://doi.org/10.1109/icpr.2016.7899768","mag":"2607930008"},"language":"en","primary_location":{"id":"doi:10.1109/icpr.2016.7899768","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2016.7899768","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 23rd International Conference on Pattern Recognition (ICPR)","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/A5028415358","display_name":"Gaurav Goswami","orcid":"https://orcid.org/0000-0003-0250-5603"},"institutions":[{"id":"https://openalex.org/I68891433","display_name":"Indian Institute of Technology Delhi","ror":"https://ror.org/049tgcd06","country_code":"IN","type":"education","lineage":["https://openalex.org/I68891433"]},{"id":"https://openalex.org/I119939252","display_name":"Indraprastha Institute of Information Technology Delhi","ror":"https://ror.org/03vfp4g33","country_code":"IN","type":"education","lineage":["https://openalex.org/I119939252"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Gaurav Goswami","raw_affiliation_strings":["IIIT, Delhi, India"],"affiliations":[{"raw_affiliation_string":"IIIT, Delhi, India","institution_ids":["https://openalex.org/I119939252","https://openalex.org/I68891433"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003836761","display_name":"Nalini Ratha","orcid":"https://orcid.org/0000-0001-7913-5722"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nalini Ratha","raw_affiliation_strings":["IBM Research, USA"],"affiliations":[{"raw_affiliation_string":"IBM Research, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011779957","display_name":"Richa Singh","orcid":"https://orcid.org/0000-0003-4060-4573"},"institutions":[{"id":"https://openalex.org/I68891433","display_name":"Indian Institute of Technology Delhi","ror":"https://ror.org/049tgcd06","country_code":"IN","type":"education","lineage":["https://openalex.org/I68891433"]},{"id":"https://openalex.org/I119939252","display_name":"Indraprastha Institute of Information Technology Delhi","ror":"https://ror.org/03vfp4g33","country_code":"IN","type":"education","lineage":["https://openalex.org/I119939252"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Richa Singh","raw_affiliation_strings":["IIIT, Delhi, India"],"affiliations":[{"raw_affiliation_string":"IIIT, Delhi, India","institution_ids":["https://openalex.org/I119939252","https://openalex.org/I68891433"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5050521702","display_name":"Mayank Vatsa","orcid":"https://orcid.org/0000-0001-5952-2274"},"institutions":[{"id":"https://openalex.org/I119939252","display_name":"Indraprastha Institute of Information Technology Delhi","ror":"https://ror.org/03vfp4g33","country_code":"IN","type":"education","lineage":["https://openalex.org/I119939252"]},{"id":"https://openalex.org/I68891433","display_name":"Indian Institute of Technology Delhi","ror":"https://ror.org/049tgcd06","country_code":"IN","type":"education","lineage":["https://openalex.org/I68891433"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Mayank Vatsa","raw_affiliation_strings":["IIIT, Delhi, India"],"affiliations":[{"raw_affiliation_string":"IIIT, Delhi, India","institution_ids":["https://openalex.org/I119939252","https://openalex.org/I68891433"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5028415358"],"corresponding_institution_ids":["https://openalex.org/I119939252","https://openalex.org/I68891433"],"apc_list":null,"apc_paid":null,"fwci":0.445,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.8154568,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1011","last_page":"1016"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9987000226974487,"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"}},"topics":[{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9987000226974487,"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/T10828","display_name":"Biometric Identification and Security","score":0.9927999973297119,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11871","display_name":"Advanced Statistical Methods and Models","score":0.9843000173568726,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.7142616510391235},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6480631828308105},{"id":"https://openalex.org/keywords/normalization","display_name":"Normalization (sociology)","score":0.6427053809165955},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6283528208732605},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.531559407711029},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.44485563039779663}],"concepts":[{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.7142616510391235},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6480631828308105},{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.6427053809165955},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6283528208732605},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.531559407711029},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44485563039779663},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C19165224","wikidata":"https://www.wikidata.org/wiki/Q23404","display_name":"Anthropology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icpr.2016.7899768","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2016.7899768","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 23rd International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.800000011920929}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W95193141","https://openalex.org/W2012942264","https://openalex.org/W2056714990","https://openalex.org/W2057888214","https://openalex.org/W2061272711","https://openalex.org/W2071789457","https://openalex.org/W2078953162","https://openalex.org/W2096942889","https://openalex.org/W2122098412","https://openalex.org/W2136885397","https://openalex.org/W2158275940","https://openalex.org/W2166290812","https://openalex.org/W2212220779","https://openalex.org/W2250624607","https://openalex.org/W2795431618","https://openalex.org/W2962714336"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W3046775127","https://openalex.org/W3107602296","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W2033914206"],"abstract_inverted_index":{"Classifier":[0],"fusion":[1,151],"is":[2,180,209],"a":[3,26,60,241],"well-studied":[4],"problem":[5,128],"in":[6,43],"which":[7],"decisions":[8],"from":[9],"multiple":[10],"classifiers":[11,34,86,231],"are":[12],"combined":[13,201],"at":[14,35,87],"the":[15,44,53,66,70,88,126,142,146,173,177,184,196,200,214,235,248],"score,":[16],"rank,":[17],"or":[18,73],"decision":[19],"level":[20],"to":[21,59,84,101,106,140,203,211,245],"obtain":[22],"better":[23],"results":[24,215],"than":[25,183],"single":[27],"classifier.":[28,75],"Subsequently,":[29],"various":[30],"techniques":[31,123,169,227],"for":[32,113,149,229],"combining":[33,65],"each":[36,57,133],"of":[37,132],"these":[38],"levels":[39],"have":[40,124],"been":[41,99],"proposed":[42],"literature.":[45],"Many":[46],"popular":[47,189],"methods":[48],"entail":[49],"scaling":[50,185],"and":[51,119,170,208,232],"normalizing":[52,234],"scores":[54,68,105],"obtained":[55,216],"by":[56,176,187,217],"classifier":[58,103,150],"common":[61],"numerical":[62],"range":[63],"before":[64],"normalized":[67],"using":[69,238,247],"sum":[71],"rule":[72],"another":[74],"In":[76,135],"this":[77,136],"research,":[78],"we":[79,144],"explore":[80],"an":[81],"alternative":[82],"method":[83],"combine":[85,141],"score":[89,121,158,202,237],"level.":[90],"The":[91,116],"Pool":[92],"Adjacent":[93],"Violators":[94],"(PAV)":[95],"algorithm":[96,118,148,179,198],"has":[97],"traditionally":[98],"utilized":[100],"convert":[102],"match":[104],"confidence":[107,207],"values":[108],"that":[109,162,172,223],"model":[110],"posterior":[111],"probabilities":[112],"test":[114],"data.":[115],"PAV":[117,147,178,197,239,249],"other":[120,188,218],"normalization":[122,190,226],"studied":[125],"same":[127],"without":[129],"being":[130],"aware":[131],"other.":[134],"first":[137,228],"ever":[138],"study":[139],"two,":[143],"propose":[145],"on":[152],"publicly":[153],"available":[154],"NIST":[155],"multi-modal":[156],"biometrics":[157],"dataset.":[159],"We":[160,220],"observe":[161,222],"it":[163],"provides":[164],"several":[165],"advantages":[166],"over":[167],"existing":[168],"find":[171],"interpretation":[174],"learned":[175,186],"more":[181],"robust":[182],"algorithms":[191],"such":[192],"as":[193,206],"min-max.":[194],"Moreover,":[195],"enables":[199],"be":[204],"interpreted":[205],"able":[210],"further":[212],"improve":[213],"approaches.":[219],"also":[221],"utilizing":[224],"traditional":[225],"individual":[230],"then":[233],"fused":[236],"offers":[240],"performance":[242],"boost":[243],"compared":[244],"only":[246],"algorithm.":[250]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}