{"id":"https://openalex.org/W2088631864","doi":"https://doi.org/10.1109/wacv.2014.6836076","title":"GMM improves the reject option in hierarchical classification for fish recognition","display_name":"GMM improves the reject option in hierarchical classification for fish recognition","publication_year":2014,"publication_date":"2014-03-01","ids":{"openalex":"https://openalex.org/W2088631864","doi":"https://doi.org/10.1109/wacv.2014.6836076","mag":"2088631864"},"language":"en","primary_location":{"id":"doi:10.1109/wacv.2014.6836076","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv.2014.6836076","pdf_url":null,"source":{"id":"https://openalex.org/S4393918690","display_name":"IEEE Winter Conference on Applications of Computer Vision","issn_l":"2472-6737","issn":["2472-6737"],"is_oa":false,"is_in_doaj":false,"is_core":false,"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":"IEEE Winter Conference on Applications of Computer Vision","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://www.research.ed.ac.uk/en/publications/cdce397a-da74-4758-b309-f951bdb65181","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5080011824","display_name":"Phoenix X. Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I98677209","display_name":"University of Edinburgh","ror":"https://ror.org/01nrxwf90","country_code":"GB","type":"education","lineage":["https://openalex.org/I98677209"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Phoenix X. Huang","raw_affiliation_strings":["School of Informatics, University of Edinburgh, Edinburgh","School of Informatics, University of Edinburgh, 10 Crichton street, UK"],"affiliations":[{"raw_affiliation_string":"School of Informatics, University of Edinburgh, Edinburgh","institution_ids":["https://openalex.org/I98677209"]},{"raw_affiliation_string":"School of Informatics, University of Edinburgh, 10 Crichton street, UK","institution_ids":["https://openalex.org/I98677209"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113494312","display_name":"Bastiaan J. Boom","orcid":null},"institutions":[{"id":"https://openalex.org/I98677209","display_name":"University of Edinburgh","ror":"https://ror.org/01nrxwf90","country_code":"GB","type":"education","lineage":["https://openalex.org/I98677209"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Bastiaan J. Boom","raw_affiliation_strings":["School of Informatics, University of Edinburgh, Edinburgh","School of Informatics, University of Edinburgh, 10 Crichton street, UK"],"affiliations":[{"raw_affiliation_string":"School of Informatics, University of Edinburgh, Edinburgh","institution_ids":["https://openalex.org/I98677209"]},{"raw_affiliation_string":"School of Informatics, University of Edinburgh, 10 Crichton street, UK","institution_ids":["https://openalex.org/I98677209"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020686179","display_name":"Robert B. Fisher","orcid":"https://orcid.org/0000-0001-6860-9371"},"institutions":[{"id":"https://openalex.org/I98677209","display_name":"University of Edinburgh","ror":"https://ror.org/01nrxwf90","country_code":"GB","type":"education","lineage":["https://openalex.org/I98677209"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Robert B. Fisher","raw_affiliation_strings":["School of Informatics, University of Edinburgh, Edinburgh","School of Informatics, University of Edinburgh, 10 Crichton street, UK"],"affiliations":[{"raw_affiliation_string":"School of Informatics, University of Edinburgh, Edinburgh","institution_ids":["https://openalex.org/I98677209"]},{"raw_affiliation_string":"School of Informatics, University of Edinburgh, 10 Crichton street, UK","institution_ids":["https://openalex.org/I98677209"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5080011824"],"corresponding_institution_ids":["https://openalex.org/I98677209"],"apc_list":null,"apc_paid":null,"fwci":13.6719,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":{"value":0.98663102,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"16","issue":null,"first_page":"371","last_page":"376"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12388","display_name":"Identification and Quantification in Food","score":0.9926000237464905,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T12388","display_name":"Identification and Quantification in Food","score":0.9926000237464905,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.948199987411499,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12697","display_name":"Water Quality Monitoring Technologies","score":0.9351000189781189,"subfield":{"id":"https://openalex.org/subfields/2312","display_name":"Water Science and Technology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7560108304023743},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6673284769058228},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.604198694229126},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5549408793449402},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.5311098694801331},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.5306270122528076},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.45811906456947327},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.452648401260376},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.4525274336338043},{"id":"https://openalex.org/keywords/hierarchy","display_name":"Hierarchy","score":0.43700116872787476},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.36785998940467834}],"concepts":[{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7560108304023743},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6673284769058228},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.604198694229126},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5549408793449402},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.5311098694801331},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.5306270122528076},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.45811906456947327},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.452648401260376},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.4525274336338043},{"id":"https://openalex.org/C31170391","wikidata":"https://www.wikidata.org/wiki/Q188619","display_name":"Hierarchy","level":2,"score":0.43700116872787476},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36785998940467834},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C34447519","wikidata":"https://www.wikidata.org/wiki/Q179522","display_name":"Market economy","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/wacv.2014.6836076","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv.2014.6836076","pdf_url":null,"source":{"id":"https://openalex.org/S4393918690","display_name":"IEEE Winter Conference on Applications of Computer Vision","issn_l":"2472-6737","issn":["2472-6737"],"is_oa":false,"is_in_doaj":false,"is_core":false,"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":"IEEE Winter Conference on Applications of Computer Vision","raw_type":"proceedings-article"},{"id":"pmh:oai:pure.ed.ac.uk:openaire/cdce397a-da74-4758-b309-f951bdb65181","is_oa":true,"landing_page_url":"https://www.research.ed.ac.uk/en/publications/cdce397a-da74-4758-b309-f951bdb65181","pdf_url":null,"source":{"id":"https://openalex.org/S4406922455","display_name":"Edinburgh Research Explorer","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Huang, P X, Boom, B J & Fisher, R B 2014, GMM improves the reject option in hierarchical classification for fish recognition. in WACV 2014: IEEE Winter Conference on Applications of Computer Vision. Institute of Electrical and Electronics Engineers, pp. 371-376. https://doi.org/10.1109/WACV.2014.6836076","raw_type":"contributionToPeriodical"},{"id":"pmh:oai:pure.ed.ac.uk:publications/cdce397a-da74-4758-b309-f951bdb65181","is_oa":false,"landing_page_url":"http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6836076","pdf_url":null,"source":{"id":"https://openalex.org/S4406922455","display_name":"Edinburgh Research Explorer","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":""}],"best_oa_location":{"id":"pmh:oai:pure.ed.ac.uk:openaire/cdce397a-da74-4758-b309-f951bdb65181","is_oa":true,"landing_page_url":"https://www.research.ed.ac.uk/en/publications/cdce397a-da74-4758-b309-f951bdb65181","pdf_url":null,"source":{"id":"https://openalex.org/S4406922455","display_name":"Edinburgh Research Explorer","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Huang, P X, Boom, B J & Fisher, R B 2014, GMM improves the reject option in hierarchical classification for fish recognition. in WACV 2014: IEEE Winter Conference on Applications of Computer Vision. Institute of Electrical and Electronics Engineers, pp. 371-376. https://doi.org/10.1109/WACV.2014.6836076","raw_type":"contributionToPeriodical"},"sustainable_development_goals":[{"display_name":"Life in Land","score":0.5,"id":"https://metadata.un.org/sdg/15"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W107021117","https://openalex.org/W1522537991","https://openalex.org/W1554663460","https://openalex.org/W1618905105","https://openalex.org/W1959000896","https://openalex.org/W2015245929","https://openalex.org/W2015749074","https://openalex.org/W2052980499","https://openalex.org/W2073711670","https://openalex.org/W2101358131","https://openalex.org/W2108598243","https://openalex.org/W2109172948","https://openalex.org/W2109189163","https://openalex.org/W2116310878","https://openalex.org/W2123304600","https://openalex.org/W2124577949","https://openalex.org/W2132308451","https://openalex.org/W2145885328","https://openalex.org/W2147675406","https://openalex.org/W2148687775","https://openalex.org/W2150766729","https://openalex.org/W2153734642","https://openalex.org/W3110719502","https://openalex.org/W4239072543","https://openalex.org/W4388297464","https://openalex.org/W6631341354","https://openalex.org/W6636501900","https://openalex.org/W6641111440","https://openalex.org/W6676297131","https://openalex.org/W6679670742","https://openalex.org/W6682003322"],"related_works":["https://openalex.org/W4388745254","https://openalex.org/W2980082554","https://openalex.org/W1517228774","https://openalex.org/W2767419625","https://openalex.org/W2389704471","https://openalex.org/W4366990902","https://openalex.org/W4317732970","https://openalex.org/W4388550696","https://openalex.org/W4321636153","https://openalex.org/W4313289487"],"abstract_inverted_index":{"A":[0],"reject":[1,147],"option":[2],"in":[3,29,170,180],"classification":[4,32,63,176],"is":[5,66,149],"useful":[6],"to":[7,16,54,69,83,125],"filter":[8],"less":[9],"confident":[10],"decisions":[11],"of":[12,61,88,93,105,129,135],"known":[13],"classes":[14],"or":[15],"detect":[17],"and":[18,97,99,110,177],"remove":[19],"untrained":[20],"classes.":[21,75,183],"This":[22,65],"paper":[23],"presents":[24],"a":[25,30,78,123,127,136,152,168],"novel":[26],"rejection":[27,48,162],"system":[28,49],"hierarchical":[31,39,157,175],"method":[33],"for":[34],"fish":[35,107],"species":[36],"recognition.":[37],"Since":[38],"methods":[40],"accumulate":[41],"errors":[42,173],"along":[43],"the":[44,47,59,62,85,106,143,146,171],"decision":[45],"path,":[46],"provides":[50],"an":[51,178],"alternative":[52],"channel":[53],"discover":[55],"misclassified":[56],"samples":[57,72,134],"at":[58],"leaves":[60],"hierarchy.":[64],"also":[67],"applied":[68],"probe":[70],"test":[71],"from":[73,102,139,174],"new":[74],"We":[76,112,159],"apply":[77],"Gaussian":[79],"Mixture":[80],"Model":[81],"(GMM)":[82],"evaluate":[84],"posterior":[86],"probability":[87],"testing":[89],"samples.":[90],"2626":[91],"dimensions":[92],"features,":[94],"e.g.":[95],"color":[96],"shape":[98],"texture":[100],"properties,":[101],"different":[103],"parts":[104],"are":[108],"computed":[109],"normalized.":[111],"use":[113],"forward":[114],"sequential":[115],"feature":[116],"selection":[117],"(FSFS),":[118],"which":[119],"utilizes":[120],"SVM":[121],"as":[122],"classifier,":[124],"select":[126],"subset":[128],"effective":[130],"features":[131],"that":[132],"distinguishes":[133],"given":[137],"class":[138],"others.":[140],"After":[141],"learning":[142],"mixture":[144],"models,":[145],"function":[148],"integrated":[150],"with":[151],"Balance-Guaranteed":[153],"Optimized":[154],"Tree":[155],"(BGOT)":[156],"method.":[158],"compare":[160],"three":[161],"methods.":[163],"The":[164],"experimental":[165],"results":[166],"demonstrate":[167],"reduction":[169],"accumulated":[172],"improvement":[179],"discovering":[181],"unknown":[182]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":3},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":3},{"year":2014,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
