{"id":"https://openalex.org/W4319068931","doi":"https://doi.org/10.1109/tsp.2023.3242091","title":"MIML-GAN: A GAN-Based Algorithm for Multi-Instance Multi-Label Learning on Overlapping Signal Waveform Recognition","display_name":"MIML-GAN: A GAN-Based Algorithm for Multi-Instance Multi-Label Learning on Overlapping Signal Waveform Recognition","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4319068931","doi":"https://doi.org/10.1109/tsp.2023.3242091"},"language":"en","primary_location":{"id":"doi:10.1109/tsp.2023.3242091","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2023.3242091","pdf_url":null,"source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Signal Processing","raw_type":"journal-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/A5004600365","display_name":"Zesi Pan","orcid":"https://orcid.org/0000-0002-4800-6984"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]},{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zesi Pan","raw_affiliation_strings":["School of Information and Electronics, Beijing Institute of Technology, Beijing, China","Peng Cheng Laboratory, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0002-4800-6984","affiliations":[{"raw_affiliation_string":"School of Information and Electronics, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]},{"raw_affiliation_string":"Peng Cheng Laboratory, Shenzhen, China","institution_ids":["https://openalex.org/I4210136793"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100408141","display_name":"Bo Wang","orcid":"https://orcid.org/0000-0002-8054-8185"},"institutions":[{"id":"https://openalex.org/I146563203","display_name":"University of International Business and Economics","ror":"https://ror.org/05khqpb71","country_code":"CN","type":"education","lineage":["https://openalex.org/I146563203"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo Wang","raw_affiliation_strings":["School of Information Technology and Management, University of International Business and Economics, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-8054-8185","affiliations":[{"raw_affiliation_string":"School of Information Technology and Management, University of International Business and Economics, Beijing, China","institution_ids":["https://openalex.org/I146563203"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101415622","display_name":"Ruibin Zhang","orcid":"https://orcid.org/0009-0002-4627-7227"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruibin Zhang","raw_affiliation_strings":["School of Information and Electronics, Beijing Institute of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0002-4627-7227","affiliations":[{"raw_affiliation_string":"School of Information and Electronics, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041312010","display_name":"Shafei Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shafei Wang","raw_affiliation_strings":["School of Information and Electronics, Beijing Institute of Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information and Electronics, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023531675","display_name":"Yunjie Li","orcid":"https://orcid.org/0000-0003-3721-0178"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]},{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunjie Li","raw_affiliation_strings":["School of Cyberspace Science and Technology, Beijing Institute of Technology, Beijing, China","School of Information and Electronics, Beijing Institute of Technology, Beijing, China","Peng Cheng Laboratory, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0003-3721-0178","affiliations":[{"raw_affiliation_string":"School of Cyberspace Science and Technology, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]},{"raw_affiliation_string":"School of Information and Electronics, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]},{"raw_affiliation_string":"Peng Cheng Laboratory, Shenzhen, China","institution_ids":["https://openalex.org/I4210136793"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101533266","display_name":"Yan Li","orcid":"https://orcid.org/0000-0001-9562-9634"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]},{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yan Li","raw_affiliation_strings":["School of Cyberspace Science and Technology, Beijing Institute of Technology, Beijing, China","School of Information and Electronics, Beijing Institute of Technology, Beijing, China","Peng Cheng Laboratory, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0001-9562-9634","affiliations":[{"raw_affiliation_string":"School of Cyberspace Science and Technology, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]},{"raw_affiliation_string":"School of Information and Electronics, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]},{"raw_affiliation_string":"Peng Cheng Laboratory, Shenzhen, China","institution_ids":["https://openalex.org/I4210136793"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":2645,"currency":"USD","value_usd":2645},"apc_paid":null,"fwci":4.9077,"has_fulltext":false,"cited_by_count":38,"citation_normalized_percentile":{"value":0.96097338,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"71","issue":null,"first_page":"859","last_page":"872"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12131","display_name":"Wireless Signal Modulation Classification","score":0.9865999817848206,"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/T12131","display_name":"Wireless Signal Modulation Classification","score":0.9865999817848206,"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/T11309","display_name":"Music and Audio Processing","score":0.9659000039100647,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.9605000019073486,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/discriminator","display_name":"Discriminator","score":0.792894184589386},{"id":"https://openalex.org/keywords/waveform","display_name":"Waveform","score":0.661347508430481},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6613068580627441},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6470025181770325},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.5581806898117065},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5273840427398682},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.4986402988433838},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.49244770407676697},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.43710559606552124},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.41864097118377686},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3418731987476349},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.28835925459861755}],"concepts":[{"id":"https://openalex.org/C2779803651","wikidata":"https://www.wikidata.org/wiki/Q5282088","display_name":"Discriminator","level":3,"score":0.792894184589386},{"id":"https://openalex.org/C197424946","wikidata":"https://www.wikidata.org/wiki/Q1165717","display_name":"Waveform","level":3,"score":0.661347508430481},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6613068580627441},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6470025181770325},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.5581806898117065},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5273840427398682},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.4986402988433838},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.49244770407676697},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.43710559606552124},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.41864097118377686},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3418731987476349},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.28835925459861755},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"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/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tsp.2023.3242091","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2023.3242091","pdf_url":null,"source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Signal Processing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6600000262260437,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G3796935045","display_name":null,"funder_award_id":"61976019","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8607756921","display_name":null,"funder_award_id":"61901032","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":61,"referenced_works":["https://openalex.org/W259550003","https://openalex.org/W1983320747","https://openalex.org/W2061526129","https://openalex.org/W2079057609","https://openalex.org/W2113741880","https://openalex.org/W2114315281","https://openalex.org/W2123958887","https://openalex.org/W2132442585","https://openalex.org/W2135533176","https://openalex.org/W2136504847","https://openalex.org/W2140147143","https://openalex.org/W2153816607","https://openalex.org/W2162531249","https://openalex.org/W2510754404","https://openalex.org/W2514741231","https://openalex.org/W2560119283","https://openalex.org/W2586095846","https://openalex.org/W2616803684","https://openalex.org/W2734578496","https://openalex.org/W2789677693","https://openalex.org/W2791587174","https://openalex.org/W2794908468","https://openalex.org/W2885073348","https://openalex.org/W2900967017","https://openalex.org/W2908997014","https://openalex.org/W2944003962","https://openalex.org/W2962738058","https://openalex.org/W2963090019","https://openalex.org/W2963250052","https://openalex.org/W2963340196","https://openalex.org/W2964275459","https://openalex.org/W2990554528","https://openalex.org/W3004075920","https://openalex.org/W3011402415","https://openalex.org/W3042290507","https://openalex.org/W3086580107","https://openalex.org/W3096831136","https://openalex.org/W3097743819","https://openalex.org/W3099204742","https://openalex.org/W3138656191","https://openalex.org/W3177019819","https://openalex.org/W3190182606","https://openalex.org/W4220983482","https://openalex.org/W4285161976","https://openalex.org/W4288966168","https://openalex.org/W4293861233","https://openalex.org/W6623329352","https://openalex.org/W6640500741","https://openalex.org/W6677082149","https://openalex.org/W6680140577","https://openalex.org/W6680434193","https://openalex.org/W6685777725","https://openalex.org/W6717434760","https://openalex.org/W6718379498","https://openalex.org/W6734384760","https://openalex.org/W6738597727","https://openalex.org/W6741832134","https://openalex.org/W6746466744","https://openalex.org/W6751661576","https://openalex.org/W6757355660","https://openalex.org/W6767433964"],"related_works":["https://openalex.org/W3093527782","https://openalex.org/W2546942002","https://openalex.org/W2970216048","https://openalex.org/W2382607599","https://openalex.org/W3162567751","https://openalex.org/W4285260836","https://openalex.org/W4221088574","https://openalex.org/W2791440580","https://openalex.org/W3094076422","https://openalex.org/W3046775127"],"abstract_inverted_index":{"Existing":[0],"studies":[1],"for":[2,49],"automatic":[3],"waveform":[4,127,217],"recognition":[5,218],"of":[6,35,83,92,108,124,140,175,193],"overlapping":[7,93,125,187],"signals":[8],"have":[9],"mostly":[10],"been":[11],"conducted":[12],"in":[13,21,61],"a":[14],"supervised":[15,24,75,215],"manner.":[16],"Although":[17],"demonstrating":[18],"superior":[19],"performance":[20],"recent":[22],"years,":[23],"methods":[25],"rely":[26],"heavily":[27],"on":[28],"sufficient":[29],"labeled":[30],"samples,":[31],"but":[32],"the":[33,47,54,62,81,84,90,100,106,121,131,134,138,141,145,150,157,161,172,176,191,194,201,211],"acquisition":[34],"annotated":[36],"data":[37,143],"is":[38,71,118],"expensive,":[39],"time-consuming,":[40],"and":[41,78,180,209,214],"sometimes":[42],"infeasible.":[43],"This":[44],"shortage":[45],"drives":[46],"need":[48],"semi-supervised":[50,213],"learning":[51,70,76,102,147],"methods,":[52],"where":[53],"unlabeled":[55],"samples":[56],"can":[57,153],"be":[58,154],"fully":[59],"exploited":[60],"training":[63,110,142],"stage.":[64],"In":[65,95],"addition,":[66],"multi-instance":[67],"multi-label":[68],"(MIML)":[69],"essentially":[72],"another":[73],"weakly":[74],"protocol,":[77],"precisely":[79],"fits":[80],"form":[82],"time-frequency":[85],"images":[86],"TFIs":[87,132],"obtained":[88],"from":[89,156],"transformation":[91],"signals.":[94],"this":[96],"paper,":[97],"delving":[98],"into":[99,133],"MIML":[101,122,162],"problem,":[103],"we":[104,169],"leverage":[105],"advantage":[107],"adversarial":[109,146],"to":[111,120],"formulate":[112],"an":[113],"effective":[114],"algorithm":[115,203],"MIML-GAN,":[116],"which":[117],"tailored":[119],"problem":[123],"signal":[126,188,216],"recognition.":[128],"After":[129],"feeding":[130],"network,":[135],"MIML-GAN":[136,177],"approximates":[137],"distribution":[139],"using":[144],"principle.":[148],"Subsequently,":[149],"bag-level":[151],"prediction":[152,159],"derived":[155],"instance-level":[158],"upon":[160],"discriminator":[163],"through":[164],"adaptive":[165],"threshold":[166],"calibration.":[167],"Specifically,":[168],"elaborately":[170],"studied":[171],"global":[173],"optimality":[174],"objective":[178],"function,":[179],"extensive":[181],"simulations":[182],"are":[183],"carried":[184],"out":[185],"with":[186],"dataset,":[189],"validating":[190],"ascendancy":[192],"proposed":[195,202],"method.":[196],"Comparative":[197],"experiments":[198],"demonstrate":[199],"that":[200],"possesses":[204],"promising":[205],"feature":[206],"representation":[207],"capability,":[208],"outperforms":[210],"existing":[212],"approaches.":[219]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":15},{"year":2024,"cited_by_count":15},{"year":2023,"cited_by_count":4}],"updated_date":"2026-08-21T09:56:20.448147","created_date":"2025-10-10T00:00:00"}