{"id":"https://openalex.org/W2744774122","doi":"https://doi.org/10.23919/icif.2017.8009691","title":"Multi-feature fusion algorithm based on generalized discriminative Multi-Set Canonical Correlation Analysis and its application for recognition","display_name":"Multi-feature fusion algorithm based on generalized discriminative Multi-Set Canonical Correlation Analysis and its application for recognition","publication_year":2017,"publication_date":"2017-07-01","ids":{"openalex":"https://openalex.org/W2744774122","doi":"https://doi.org/10.23919/icif.2017.8009691","mag":"2744774122"},"language":"en","primary_location":{"id":"doi:10.23919/icif.2017.8009691","is_oa":false,"landing_page_url":"https://doi.org/10.23919/icif.2017.8009691","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 20th International Conference on Information Fusion (Fusion)","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/A5037885387","display_name":"Yihai Liu","orcid":"https://orcid.org/0000-0001-5404-5931"},"institutions":[{"id":"https://openalex.org/I4210118629","display_name":"NARI Group (China)","ror":"https://ror.org/02egn3136","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210118629"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yihai Liu","raw_affiliation_strings":["Jiangsu Automation Research Institute, Lianyungang, China"],"affiliations":[{"raw_affiliation_string":"Jiangsu Automation Research Institute, Lianyungang, China","institution_ids":["https://openalex.org/I4210118629"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103572030","display_name":"Jiazhou He","orcid":"https://orcid.org/0009-0005-1222-9472"},"institutions":[{"id":"https://openalex.org/I4210118629","display_name":"NARI Group (China)","ror":"https://ror.org/02egn3136","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210118629"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiazhou He","raw_affiliation_strings":["Jiangsu Automation Research Institute, Lianyungang, China"],"affiliations":[{"raw_affiliation_string":"Jiangsu Automation Research Institute, Lianyungang, China","institution_ids":["https://openalex.org/I4210118629"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007601669","display_name":"Chun-Shan Ding","orcid":null},"institutions":[{"id":"https://openalex.org/I4210118629","display_name":"NARI Group (China)","ror":"https://ror.org/02egn3136","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210118629"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chunshan Ding","raw_affiliation_strings":["Jiangsu Automation Research Institute, Lianyungang, China"],"affiliations":[{"raw_affiliation_string":"Jiangsu Automation Research Institute, Lianyungang, China","institution_ids":["https://openalex.org/I4210118629"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5037885387"],"corresponding_institution_ids":["https://openalex.org/I4210118629"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.10435977,"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":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9900000095367432,"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/T10057","display_name":"Face and Expression Recognition","score":0.9900000095367432,"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/T14257","display_name":"Advanced Measurement and Detection Methods","score":0.9642999768257141,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12389","display_name":"Infrared Target Detection Methodologies","score":0.9399999976158142,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.8821679353713989},{"id":"https://openalex.org/keywords/canonical-correlation","display_name":"Canonical correlation","score":0.8003932237625122},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7232260704040527},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6727504730224609},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6658607721328735},{"id":"https://openalex.org/keywords/projection","display_name":"Projection (relational algebra)","score":0.6349600553512573},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.6305107474327087},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5909230709075928},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.540124237537384},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.5301535725593567},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5162855982780457},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.4495186507701874},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.36086222529411316},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3209426999092102}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.8821679353713989},{"id":"https://openalex.org/C153874254","wikidata":"https://www.wikidata.org/wiki/Q115542","display_name":"Canonical correlation","level":2,"score":0.8003932237625122},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7232260704040527},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6727504730224609},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6658607721328735},{"id":"https://openalex.org/C57493831","wikidata":"https://www.wikidata.org/wiki/Q3134666","display_name":"Projection (relational algebra)","level":2,"score":0.6349600553512573},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.6305107474327087},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5909230709075928},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.540124237537384},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.5301535725593567},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5162855982780457},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.4495186507701874},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.36086222529411316},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3209426999092102},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/icif.2017.8009691","is_oa":false,"landing_page_url":"https://doi.org/10.23919/icif.2017.8009691","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 20th International Conference on Information Fusion (Fusion)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.7699999809265137}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W1963631516","https://openalex.org/W1975077471","https://openalex.org/W2029420083","https://openalex.org/W2060794592","https://openalex.org/W2096663965","https://openalex.org/W2110455444","https://openalex.org/W2347602515","https://openalex.org/W3120740533"],"related_works":["https://openalex.org/W2965546495","https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W2093195256","https://openalex.org/W2154562908","https://openalex.org/W2132659060","https://openalex.org/W2031992971","https://openalex.org/W3214791684","https://openalex.org/W2353265673","https://openalex.org/W2152662039"],"abstract_inverted_index":{"Feature":[0],"fusion":[1,40,70,109,114],"plays":[2],"an":[3],"important":[4],"role":[5],"in":[6,35,39,56],"target":[7],"recognition,":[8],"especially":[9],"when":[10],"single":[11],"sensor's":[12],"recognition":[13,115],"capability":[14],"is":[15,54,100],"limited":[16],"under":[17,111],"severe":[18],"situations.":[19],"In":[20],"view":[21],"of":[22,24,49,64],"shortcomings":[23],"Multi-set":[25],"Canonical":[26],"Correlation":[27],"Analysis":[28],"(MCCA)":[29],"and":[30,84,87,103],"its":[31],"supervised":[32],"modified":[33],"methods":[34,110],"using":[36],"category":[37],"information":[38],"projection":[41,66],"rule":[42],"learning,":[43],"a":[44,62],"generalized":[45],"discriminative":[46],"learning":[47],"version":[48],"MCCA,":[50],"termed":[51],"as":[52],"GDMCCA,":[53],"proposed":[55,98],"this":[57],"paper.":[58],"GDMCCA":[59],"can":[60,77],"find":[61],"set":[63,76],"optimal":[65],"vector":[67],"for":[68],"feature":[69,75,108],"such":[71],"that":[72,96],"the":[73,80,89,97,112],"fused":[74],"simultaneously":[78],"maximize":[79],"difference":[81],"between":[82],"within-class":[83,92],"between-class":[85],"correlation":[86],"minimize":[88],"total":[90],"samples'":[91],"scatter.":[93],"Results":[94],"show":[95],"algorithm":[99],"more":[101],"effective":[102],"robust":[104],"than":[105],"other":[106],"related":[107],"same":[113],"scenarios.":[116]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
