{"id":"https://openalex.org/W4366386351","doi":"https://doi.org/10.1109/tim.2023.3268454","title":"PaCNN-LSTM: A Localization Scheme Based on Improved Contrastive Learning and Parallel Fusion Neural Network","display_name":"PaCNN-LSTM: A Localization Scheme Based on Improved Contrastive Learning and Parallel Fusion Neural Network","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4366386351","doi":"https://doi.org/10.1109/tim.2023.3268454"},"language":"en","primary_location":{"id":"doi:10.1109/tim.2023.3268454","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2023.3268454","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"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 Instrumentation and Measurement","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/A5088606308","display_name":"Qiaolin Pu","orcid":"https://orcid.org/0000-0002-9357-6003"},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Qiaolin Pu","raw_affiliation_strings":["School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China"],"raw_orcid":"https://orcid.org/0000-0002-9357-6003","affiliations":[{"raw_affiliation_string":"School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China","institution_ids":["https://openalex.org/I10535382"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107948875","display_name":"Mu Zhou","orcid":"https://orcid.org/0000-0002-0840-9084"},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Youkun Chen","raw_affiliation_strings":["School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China"],"raw_orcid":"https://orcid.org/0000-0002-0840-9084","affiliations":[{"raw_affiliation_string":"School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China","institution_ids":["https://openalex.org/I10535382"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037835022","display_name":"Mu Zhou","orcid":"https://orcid.org/0000-0003-3533-2227"},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mu Zhou","raw_affiliation_strings":["School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China"],"raw_orcid":"https://orcid.org/0000-0003-3533-2227","affiliations":[{"raw_affiliation_string":"School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China","institution_ids":["https://openalex.org/I10535382"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012777103","display_name":"Joseph Kee\u2010Yin Ng","orcid":"https://orcid.org/0000-0001-8286-4344"},"institutions":[{"id":"https://openalex.org/I141568987","display_name":"Hong Kong Baptist University","ror":"https://ror.org/0145fw131","country_code":"HK","type":"education","lineage":["https://openalex.org/I141568987"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Joseph Kee-Yin Ng","raw_affiliation_strings":["Department of Computer Science, Hong Kong Baptist University, Kowloon Tong, Hong Kong"],"raw_orcid":"https://orcid.org/0000-0001-8286-4344","affiliations":[{"raw_affiliation_string":"Department of Computer Science, Hong Kong Baptist University, Kowloon Tong, Hong Kong","institution_ids":["https://openalex.org/I141568987"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5075683477","display_name":"Jinyu Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinyu Zhang","raw_affiliation_strings":["School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China"],"raw_orcid":"https://orcid.org/0000-0002-6334-0745","affiliations":[{"raw_affiliation_string":"School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China","institution_ids":["https://openalex.org/I10535382"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5088606308"],"corresponding_institution_ids":["https://openalex.org/I10535382"],"apc_list":null,"apc_paid":null,"fwci":0.7642,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.70186714,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"72","issue":null,"first_page":"1","last_page":"11"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":1.0,"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/T11739","display_name":"Microwave Imaging and Scattering Analysis","score":0.998199999332428,"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":0.9980000257492065,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8101247549057007},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.7248666882514954},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.6882368326187134},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6882032752037048},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6475329399108887},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6425625681877136},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6143420338630676},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5896041989326477},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5416995882987976},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.45009854435920715},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.4332853853702545},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.34090548753738403},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3201158344745636}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8101247549057007},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.7248666882514954},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6882368326187134},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6882032752037048},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6475329399108887},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6425625681877136},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6143420338630676},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5896041989326477},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5416995882987976},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.45009854435920715},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.4332853853702545},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34090548753738403},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3201158344745636},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","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/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tim.2023.3268454","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2023.3268454","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"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 Instrumentation and Measurement","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.5199999809265137,"display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G1711489774","display_name":null,"funder_award_id":"62201110","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2428775799","display_name":null,"funder_award_id":"CSTB2022NSCQ-MSX0895","funder_id":"https://openalex.org/F4320323172","funder_display_name":"Natural Science Foundation of Chongqing"},{"id":"https://openalex.org/G3867746544","display_name":null,"funder_award_id":"KJQN202200648","funder_id":"https://openalex.org/F4320324805","funder_display_name":"Chongqing Municipal Education Commission"},{"id":"https://openalex.org/G8045795237","display_name":null,"funder_award_id":"CSTB2022NSCQ-MSX1385","funder_id":"https://openalex.org/F4320323172","funder_display_name":"Natural Science Foundation of Chongqing"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320323172","display_name":"Natural Science Foundation of Chongqing","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320324805","display_name":"Chongqing Municipal Education Commission","ror":"https://ror.org/031nm5713"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W1947481528","https://openalex.org/W2138621090","https://openalex.org/W2791204295","https://openalex.org/W2886522435","https://openalex.org/W2903835995","https://openalex.org/W2911437338","https://openalex.org/W2969549094","https://openalex.org/W2972475635","https://openalex.org/W2981907391","https://openalex.org/W2991570458","https://openalex.org/W2996316805","https://openalex.org/W3019863049","https://openalex.org/W3026106375","https://openalex.org/W3029393543","https://openalex.org/W3032084226","https://openalex.org/W3035419842","https://openalex.org/W3088056166","https://openalex.org/W3089619751","https://openalex.org/W3094620144","https://openalex.org/W3114364338","https://openalex.org/W3115024088","https://openalex.org/W3133149221","https://openalex.org/W3148507835","https://openalex.org/W3191506988","https://openalex.org/W3197942267","https://openalex.org/W3199396846","https://openalex.org/W3214186435","https://openalex.org/W4205273301","https://openalex.org/W4205552735","https://openalex.org/W4205875171","https://openalex.org/W4206199846","https://openalex.org/W4206219710","https://openalex.org/W4207073963","https://openalex.org/W4226165900","https://openalex.org/W4285285502","https://openalex.org/W4308580603","https://openalex.org/W4360907446","https://openalex.org/W6776700526"],"related_works":["https://openalex.org/W2953234277","https://openalex.org/W2626256601","https://openalex.org/W147410782","https://openalex.org/W4401096132","https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3103566983","https://openalex.org/W3029198973"],"abstract_inverted_index":{"The":[0,21],"deep":[1,16],"learning":[2,83,102],"technique":[3],"plays":[4],"an":[5,69,80],"important":[6],"role":[7],"in":[8,31,144],"Wi-Fi":[9,71],"localization":[10,72,205],"systems":[11],"as":[12,122],"it":[13,168],"could":[14],"mine":[15],"features":[17,162],"of":[18,33,42,101,154,163,174,194,207],"measurement":[19],"data.":[20],"main":[22],"challenges":[23],"are":[24,51],"to":[25,37,54,61,86,92],"combat":[26],"the":[27,39,46,55,63,88,94,99,107,151,158,171,188,191,204,208,216],"signal":[28,90,164],"fluctuation":[29],"resulting":[30],"decrease":[32],"sample":[34,43,89],"discrimination,":[35],"and":[36,58,103,105,130,160],"leverage":[38],"broadest":[40],"information":[41,177,193],"measurements":[44,91],"during":[45],"training":[47],"phase,":[48],"since":[49],"they":[50],"directly":[52],"related":[53],"location":[56,217],"accuracy":[57,218],"robustness.":[59],"Hence,":[60],"address":[62],"above":[64],"issues,":[65],"this":[66],"paper":[67],"proposes":[68],"indoor":[70],"scheme":[73,210],"which":[74,149],"mainly":[75],"contains":[76],"two":[77],"modules.":[78],"Firstly,":[79],"improved":[81,220],"contrastive":[82],"is":[84,97,179,211,219],"introduced":[85],"handle":[87],"increase":[93],"discrimination.":[95],"It":[96],"from":[98],"perspective":[100],"encoding,":[104],"avoids":[106],"drawbacks":[108],"brought":[109],"by":[110,221],"traditional":[111],"processing":[112],"methods.":[113],"Then,":[114],"we":[115],"build":[116],"a":[117,184],"parallel":[118,145],"fusion":[119],"network":[120,128,134],"named":[121],"PaCNN-LSTM":[123,140],"based":[124],"on":[125],"convolutional":[126],"neural":[127,142],"(CNN)":[129],"long":[131],"short-term":[132],"memory":[133],"(LSTM).":[135],"Compared":[136],"with":[137],"existing":[138],"networks,":[139],"connects":[141],"networks":[143],"rather":[146],"than":[147,213],"serial,":[148],"improves":[150],"generalization":[152],"performance":[153,206],"model":[155],"when":[156],"extracting":[157],"spatial":[159],"temporal":[161],"measurements.":[165],"In":[166],"addition,":[167],"also":[169],"considers":[170],"large":[172],"amount":[173],"middle":[175],"layer":[176,186],"that":[178,203],"always":[180],"ignored.":[181],"By":[182],"adding":[183],"Flatten":[185],"after":[187],"pooling":[189],"layer,":[190],"available":[192],"samples":[195],"has":[196],"been":[197],"broadened.":[198],"Extensive":[199],"experimental":[200],"results":[201],"show":[202],"proposed":[209],"outperformed":[212],"others,":[214],"where":[215],"about":[222],"22%.":[223]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2}],"updated_date":"2026-04-29T09:16:38.111599","created_date":"2025-10-10T00:00:00"}