{"id":"https://openalex.org/W2213436853","doi":"https://doi.org/10.1109/eusipco.2015.7362367","title":"Variational Gaussian process for sensor fusion","display_name":"Variational Gaussian process for sensor fusion","publication_year":2015,"publication_date":"2015-08-01","ids":{"openalex":"https://openalex.org/W2213436853","doi":"https://doi.org/10.1109/eusipco.2015.7362367","mag":"2213436853"},"language":"en","primary_location":{"id":"doi:10.1109/eusipco.2015.7362367","is_oa":false,"landing_page_url":"https://doi.org/10.1109/eusipco.2015.7362367","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 23rd European Signal Processing Conference (EUSIPCO)","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/A5062626628","display_name":"Neda Rohani","orcid":"https://orcid.org/0000-0002-3437-6183"},"institutions":[{"id":"https://openalex.org/I111979921","display_name":"Northwestern University","ror":"https://ror.org/000e0be47","country_code":"US","type":"education","lineage":["https://openalex.org/I111979921"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Neda Rohani","raw_affiliation_strings":["Dpt. of Electrical Engineering and Computer Science, Northwestern University, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dpt. of Electrical Engineering and Computer Science, Northwestern University, USA","institution_ids":["https://openalex.org/I111979921"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087007642","display_name":"Pablo Ruiz","orcid":"https://orcid.org/0000-0003-0381-0212"},"institutions":[{"id":"https://openalex.org/I173304897","display_name":"Universidad de Granada","ror":"https://ror.org/04njjy449","country_code":"ES","type":"education","lineage":["https://openalex.org/I173304897"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Pablo Ruiz","raw_affiliation_strings":["Dpto. de Ciencias de la Computaci\u00f3n e I.A, Universidad de Granada, Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dpto. de Ciencias de la Computaci\u00f3n e I.A, Universidad de Granada, Spain","institution_ids":["https://openalex.org/I173304897"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058786380","display_name":"Emre Besler","orcid":"https://orcid.org/0000-0001-9274-2500"},"institutions":[{"id":"https://openalex.org/I111979921","display_name":"Northwestern University","ror":"https://ror.org/000e0be47","country_code":"US","type":"education","lineage":["https://openalex.org/I111979921"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Emre Besler","raw_affiliation_strings":["Dpt. of Electrical Engineering and Computer Science, Northwestern University, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dpt. of Electrical Engineering and Computer Science, Northwestern University, USA","institution_ids":["https://openalex.org/I111979921"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023830568","display_name":"Rafael Molina","orcid":"https://orcid.org/0000-0003-4694-8588"},"institutions":[{"id":"https://openalex.org/I173304897","display_name":"Universidad de Granada","ror":"https://ror.org/04njjy449","country_code":"ES","type":"education","lineage":["https://openalex.org/I173304897"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Rafael Molina","raw_affiliation_strings":["Dpto. de Ciencias de la Computaci\u00f3n e I.A, Universidad de Granada, Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dpto. de Ciencias de la Computaci\u00f3n e I.A, Universidad de Granada, Spain","institution_ids":["https://openalex.org/I173304897"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5048650003","display_name":"Aggelos K. Katsaggelos","orcid":"https://orcid.org/0000-0003-4554-0070"},"institutions":[{"id":"https://openalex.org/I111979921","display_name":"Northwestern University","ror":"https://ror.org/000e0be47","country_code":"US","type":"education","lineage":["https://openalex.org/I111979921"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Aggelos K. Katsaggelos","raw_affiliation_strings":["Dpt. of Electrical Engineering and Computer Science, Northwestern University, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dpt. of Electrical Engineering and Computer Science, Northwestern University, USA","institution_ids":["https://openalex.org/I111979921"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.7807,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.89027719,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"16","issue":null,"first_page":"170","last_page":"174"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9998000264167786,"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9998000264167786,"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/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9890999794006348,"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/T11236","display_name":"Control Systems and Identification","score":0.9362000226974487,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/gaussian-process","display_name":"Gaussian process","score":0.6842279434204102},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6648253202438354},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.6383680105209351},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5971771478652954},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.55987548828125},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5466008186340332},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5317676663398743},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.517989993095398},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4879547953605652},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.46566227078437805},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.46546435356140137},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.4454444944858551},{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.4100600779056549},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.40479302406311035}],"concepts":[{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.6842279434204102},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6648253202438354},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.6383680105209351},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5971771478652954},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.55987548828125},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5466008186340332},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5317676663398743},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.517989993095398},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4879547953605652},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.46566227078437805},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.46546435356140137},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4454444944858551},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.4100600779056549},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.40479302406311035},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/eusipco.2015.7362367","is_oa":false,"landing_page_url":"https://doi.org/10.1109/eusipco.2015.7362367","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 23rd European Signal Processing Conference (EUSIPCO)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1548013040","https://openalex.org/W1595039761","https://openalex.org/W1663973292","https://openalex.org/W1746819321","https://openalex.org/W1996278632","https://openalex.org/W2078604986","https://openalex.org/W2095654324","https://openalex.org/W2130283669","https://openalex.org/W2140115545","https://openalex.org/W2154455818","https://openalex.org/W2160215259","https://openalex.org/W2168361149","https://openalex.org/W2251311344","https://openalex.org/W2594639291","https://openalex.org/W2951675424","https://openalex.org/W4211049957","https://openalex.org/W6679226052","https://openalex.org/W6681011923","https://openalex.org/W6682494755","https://openalex.org/W6691776783"],"related_works":["https://openalex.org/W4380150146","https://openalex.org/W3024870410","https://openalex.org/W2410652950","https://openalex.org/W4283773154","https://openalex.org/W3139174110","https://openalex.org/W4289597203","https://openalex.org/W2085630472","https://openalex.org/W1977098485","https://openalex.org/W4285201053","https://openalex.org/W4214574858"],"abstract_inverted_index":{"In":[0,92],"this":[1,82],"paper,":[2],"we":[3,96],"introduce":[4],"a":[5,46,86],"new":[6,90],"Gaussian":[7],"Process":[8],"(GP)":[9],"classification":[10,38],"method":[11,104],"for":[12],"multisensory":[13],"data.":[14,24],"The":[15],"proposed":[16,103],"approach":[17],"can":[18],"deal":[19],"with":[20],"noisy":[21],"and":[22,57,79,108,111],"missing":[23],"It":[25],"is":[26],"also":[27],"capable":[28],"of":[29,33,62,101],"estimating":[30],"the":[31,37,51,59,63,73,93,98,102],"contribution":[32],"each":[34,76,89],"sensor":[35],"towards":[36],"task.":[39],"We":[40],"use":[41],"Bayesian":[42,67],"modeling":[43],"to":[44,84,88,115],"build":[45],"GP-based":[47],"classifier":[48],"which":[49],"combines":[50],"information":[52,83],"provided":[53],"by":[54],"all":[55],"sensors":[56],"approximates":[58],"posterior":[60],"distribution":[61],"GP":[64],"using":[65],"variational":[66],"inference.":[68],"During":[69],"its":[70,113],"training":[71],"phase,":[72],"algorithm":[74],"estimates":[75],"sensor's":[77],"weight":[78],"then":[80],"uses":[81],"assign":[85],"label":[87],"sample.":[91],"experimental":[94],"section,":[95],"evaluate":[97],"classiication":[99],"performance":[100],"on":[105],"both":[106],"synthetic":[107],"real":[109],"data":[110],"show":[112],"applicability":[114],"different":[116],"scenarios.":[117]},"counts_by_year":[{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}