{"id":"https://openalex.org/W4206469465","doi":"https://doi.org/10.23919/eusipco54536.2021.9616066","title":"Multi-Sensor Fusion Framework using Discriminative Autoencoders","display_name":"Multi-Sensor Fusion Framework using Discriminative Autoencoders","publication_year":2021,"publication_date":"2021-08-23","ids":{"openalex":"https://openalex.org/W4206469465","doi":"https://doi.org/10.23919/eusipco54536.2021.9616066"},"language":"en","primary_location":{"id":"doi:10.23919/eusipco54536.2021.9616066","is_oa":false,"landing_page_url":"https://doi.org/10.23919/eusipco54536.2021.9616066","pdf_url":null,"source":{"id":"https://openalex.org/S4363607854","display_name":"2021 29th European Signal Processing Conference (EUSIPCO)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 29th 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/A5012031382","display_name":"Arup Kumar Das","orcid":"https://orcid.org/0000-0001-5367-2466"},"institutions":[{"id":"https://openalex.org/I55215948","display_name":"Tata Consultancy Services (India)","ror":"https://ror.org/01b9n8m42","country_code":"IN","type":"company","lineage":["https://openalex.org/I4210086519","https://openalex.org/I55215948"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Arup Kumar Das","raw_affiliation_strings":["TCS Research, India"],"affiliations":[{"raw_affiliation_string":"TCS Research, India","institution_ids":["https://openalex.org/I55215948"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087568042","display_name":"Kriti Kumar","orcid":"https://orcid.org/0000-0003-0484-7404"},"institutions":[{"id":"https://openalex.org/I55215948","display_name":"Tata Consultancy Services (India)","ror":"https://ror.org/01b9n8m42","country_code":"IN","type":"company","lineage":["https://openalex.org/I4210086519","https://openalex.org/I55215948"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Kriti Kumar","raw_affiliation_strings":["TCS Research, India"],"affiliations":[{"raw_affiliation_string":"TCS Research, India","institution_ids":["https://openalex.org/I55215948"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020310463","display_name":"Angshul Majumdar","orcid":"https://orcid.org/0000-0002-1065-3000"},"institutions":[{"id":"https://openalex.org/I55215948","display_name":"Tata Consultancy Services (India)","ror":"https://ror.org/01b9n8m42","country_code":"IN","type":"company","lineage":["https://openalex.org/I4210086519","https://openalex.org/I55215948"]},{"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":"Angshul Majumdar","raw_affiliation_strings":["IIIT Delhi, New Delhi, India","TCS Research, India"],"affiliations":[{"raw_affiliation_string":"IIIT Delhi, New Delhi, India","institution_ids":["https://openalex.org/I119939252","https://openalex.org/I68891433"]},{"raw_affiliation_string":"TCS Research, India","institution_ids":["https://openalex.org/I55215948"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102988572","display_name":"Saurabh Sahu","orcid":"https://orcid.org/0000-0001-6222-1587"},"institutions":[{"id":"https://openalex.org/I55215948","display_name":"Tata Consultancy Services (India)","ror":"https://ror.org/01b9n8m42","country_code":"IN","type":"company","lineage":["https://openalex.org/I4210086519","https://openalex.org/I55215948"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Saurabh Sahu","raw_affiliation_strings":["TCS Research, India"],"affiliations":[{"raw_affiliation_string":"TCS Research, India","institution_ids":["https://openalex.org/I55215948"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035666448","display_name":"M Girish Chandra","orcid":"https://orcid.org/0000-0002-1479-0504"},"institutions":[{"id":"https://openalex.org/I55215948","display_name":"Tata Consultancy Services (India)","ror":"https://ror.org/01b9n8m42","country_code":"IN","type":"company","lineage":["https://openalex.org/I4210086519","https://openalex.org/I55215948"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"M Girish Chandra","raw_affiliation_strings":["TCS Research, India"],"affiliations":[{"raw_affiliation_string":"TCS Research, India","institution_ids":["https://openalex.org/I55215948"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5012031382"],"corresponding_institution_ids":["https://openalex.org/I55215948"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.27754997,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1351","last_page":"1355"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.9922000169754028,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.9922000169754028,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/T10860","display_name":"Speech and Audio Processing","score":0.9878000020980835,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9860000014305115,"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/discriminative-model","display_name":"Discriminative model","score":0.8833990693092346},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.8285568356513977},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.787615180015564},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7343398332595825},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6925753355026245},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6362690329551697},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6182428598403931},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.46756038069725037},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.4341864585876465},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.4195873439311981},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.34069231152534485}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.8833990693092346},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.8285568356513977},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.787615180015564},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7343398332595825},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6925753355026245},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6362690329551697},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6182428598403931},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.46756038069725037},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.4341864585876465},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.4195873439311981},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.34069231152534485},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/eusipco54536.2021.9616066","is_oa":false,"landing_page_url":"https://doi.org/10.23919/eusipco54536.2021.9616066","pdf_url":null,"source":{"id":"https://openalex.org/S4363607854","display_name":"2021 29th European Signal Processing Conference (EUSIPCO)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 29th European Signal Processing Conference (EUSIPCO)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.7799999713897705,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W1967352108","https://openalex.org/W2002748000","https://openalex.org/W2005482491","https://openalex.org/W2038420319","https://openalex.org/W2100495367","https://openalex.org/W2118542129","https://openalex.org/W2133297572","https://openalex.org/W2154495931","https://openalex.org/W2163922914","https://openalex.org/W2164636120","https://openalex.org/W2184188583","https://openalex.org/W2480364715","https://openalex.org/W2549994478","https://openalex.org/W2601590138","https://openalex.org/W2603304445","https://openalex.org/W2734779477","https://openalex.org/W2740570963","https://openalex.org/W2791694051","https://openalex.org/W2808611867","https://openalex.org/W2883657838","https://openalex.org/W2889162782","https://openalex.org/W2899542484","https://openalex.org/W2931065213","https://openalex.org/W2962853966","https://openalex.org/W2964300371","https://openalex.org/W2985076077","https://openalex.org/W2999010483","https://openalex.org/W3000092951","https://openalex.org/W3006587358","https://openalex.org/W3024865103","https://openalex.org/W3086040927","https://openalex.org/W3110422146","https://openalex.org/W4293877733","https://openalex.org/W6686207219","https://openalex.org/W6705072498"],"related_works":["https://openalex.org/W4321789545","https://openalex.org/W2132659060","https://openalex.org/W2031992971","https://openalex.org/W3214791684","https://openalex.org/W2353265673","https://openalex.org/W2031175860","https://openalex.org/W2152662039","https://openalex.org/W2726747157","https://openalex.org/W2010131506","https://openalex.org/W2392133813"],"abstract_inverted_index":{"The":[0,33,51,114],"paper":[1],"presents":[2],"a":[3,13,44,61],"framework":[4,83,108],"for":[5,26,65,74,86],"multi-sensor":[6],"fusion":[7,107],"using":[8],"discriminative":[9,118],"autoencoders.":[10],"It":[11],"employs":[12],"two":[14,87],"stage":[15,56],"network":[16],"where":[17],"in":[18,47,111],"the":[19,48,76,97,103,106,124,134],"first":[20],"stage,":[21],"dedicated":[22],"autoencoders":[23,77],"are":[24,40],"learnt":[25,122],"each":[27],"sensor":[28],"to":[29,42,59,120],"obtain":[30],"sensor-specific":[31],"representations.":[32],"corresponding":[34],"latent":[35,52],"representations":[36],"from":[37,91,123],"all":[38],"sensors":[39],"combined":[41],"learn":[43,60],"fusing":[45],"autoencoder":[46],"second":[49],"stage.":[50],"representation":[53],"of":[54,105],"this":[55],"is":[57,72,84,100,109],"used":[58],"label":[62],"consistent":[63],"classifier":[64,79],"multi-class":[66],"classification.":[67],"A":[68],"joint":[69,115],"optimization":[70,116],"technique":[71],"presented":[73],"learning":[75],"and":[78,94,127],"weights":[80],"together.":[81],"This":[82],"tested":[85],"real":[88],"life":[89],"scenarios":[90],"different":[92,125],"domains":[93],"comparisons":[95],"with":[96,137],"state-of-the-art":[98,135],"techniques":[99],"presented.":[101],"Additionally,":[102],"robustness":[104],"demonstrated":[110],"noisy":[112],"environments.":[113],"allows":[117],"features":[119],"be":[121],"sensors,":[126],"hence":[128],"it":[129],"displays":[130],"superior":[131],"performance":[132],"than":[133],"methods":[136],"reduced":[138],"complexity.":[139]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}