{"id":"https://openalex.org/W4290993985","doi":"https://doi.org/10.1109/icc45855.2022.9839217","title":"Few-Shot Transfer Learning for Device-Free Fingerprinting Indoor Localization","display_name":"Few-Shot Transfer Learning for Device-Free Fingerprinting Indoor Localization","publication_year":2022,"publication_date":"2022-05-16","ids":{"openalex":"https://openalex.org/W4290993985","doi":"https://doi.org/10.1109/icc45855.2022.9839217"},"language":"en","primary_location":{"id":"doi:10.1109/icc45855.2022.9839217","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc45855.2022.9839217","pdf_url":null,"source":{"id":"https://openalex.org/S4363607711","display_name":"ICC 2022 - IEEE International Conference on Communications","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":"ICC 2022 - IEEE International Conference on Communications","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/A5044622890","display_name":"Bing-Jia Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I4210086894","display_name":"Research Center for Information Technology Innovation, Academia Sinica","ror":"https://ror.org/000zgvm20","country_code":"TW","type":"facility","lineage":["https://openalex.org/I4210086894","https://openalex.org/I84653119"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Bing-Jia Chen","raw_affiliation_strings":["Academia Sinica,Research Center for Information Technology Innovation,Taiwan","Research Center for Information Technology Innovation, Academia Sinica, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Academia Sinica,Research Center for Information Technology Innovation,Taiwan","institution_ids":["https://openalex.org/I4210086894"]},{"raw_affiliation_string":"Research Center for Information Technology Innovation, Academia Sinica, Taiwan","institution_ids":["https://openalex.org/I4210086894"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5052576795","display_name":"Ronald Y. Chang","orcid":"https://orcid.org/0000-0003-4620-6824"},"institutions":[{"id":"https://openalex.org/I4210086894","display_name":"Research Center for Information Technology Innovation, Academia Sinica","ror":"https://ror.org/000zgvm20","country_code":"TW","type":"facility","lineage":["https://openalex.org/I4210086894","https://openalex.org/I84653119"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Ronald Y. Chang","raw_affiliation_strings":["Academia Sinica,Research Center for Information Technology Innovation,Taiwan","Research Center for Information Technology Innovation, Academia Sinica, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Academia Sinica,Research Center for Information Technology Innovation,Taiwan","institution_ids":["https://openalex.org/I4210086894"]},{"raw_affiliation_string":"Research Center for Information Technology Innovation, Academia Sinica, Taiwan","institution_ids":["https://openalex.org/I4210086894"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":6.379,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":{"value":0.98266575,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"4631","last_page":"4636"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9840999841690063,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9767000079154968,"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/computer-science","display_name":"Computer science","score":0.8310165405273438},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.7661027908325195},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6860872507095337},{"id":"https://openalex.org/keywords/fingerprint","display_name":"Fingerprint (computing)","score":0.6379132270812988},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5706703662872314},{"id":"https://openalex.org/keywords/data-collection","display_name":"Data collection","score":0.4731769859790802},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.457361102104187},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.45017409324645996},{"id":"https://openalex.org/keywords/labeled-data","display_name":"Labeled data","score":0.44118884205818176},{"id":"https://openalex.org/keywords/shot","display_name":"Shot (pellet)","score":0.42992109060287476},{"id":"https://openalex.org/keywords/internet-of-things","display_name":"Internet of Things","score":0.42976099252700806},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3666205108165741},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3446946144104004},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.14565187692642212},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.09883925318717957}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8310165405273438},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.7661027908325195},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6860872507095337},{"id":"https://openalex.org/C2777826928","wikidata":"https://www.wikidata.org/wiki/Q3745713","display_name":"Fingerprint (computing)","level":2,"score":0.6379132270812988},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5706703662872314},{"id":"https://openalex.org/C133462117","wikidata":"https://www.wikidata.org/wiki/Q4929239","display_name":"Data collection","level":2,"score":0.4731769859790802},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.457361102104187},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.45017409324645996},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.44118884205818176},{"id":"https://openalex.org/C2778344882","wikidata":"https://www.wikidata.org/wiki/Q278938","display_name":"Shot (pellet)","level":2,"score":0.42992109060287476},{"id":"https://openalex.org/C81860439","wikidata":"https://www.wikidata.org/wiki/Q251212","display_name":"Internet of Things","level":2,"score":0.42976099252700806},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3666205108165741},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3446946144104004},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.14565187692642212},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.09883925318717957},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"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/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icc45855.2022.9839217","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc45855.2022.9839217","pdf_url":null,"source":{"id":"https://openalex.org/S4363607711","display_name":"ICC 2022 - IEEE International Conference on Communications","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":"ICC 2022 - IEEE International Conference on Communications","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.5600000023841858,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320322108","display_name":"Ministry of Science and Technology","ror":"https://ror.org/032e49973"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W2089695767","https://openalex.org/W2165698076","https://openalex.org/W2309512289","https://openalex.org/W2601450892","https://openalex.org/W2753857670","https://openalex.org/W2916637386","https://openalex.org/W2922174720","https://openalex.org/W2943605315","https://openalex.org/W2963341924","https://openalex.org/W2963539531","https://openalex.org/W2963943197","https://openalex.org/W2964051675","https://openalex.org/W2964321699","https://openalex.org/W2991221840","https://openalex.org/W3034942609","https://openalex.org/W3043789091","https://openalex.org/W3047491762","https://openalex.org/W3090781815","https://openalex.org/W3121381145","https://openalex.org/W3126469890","https://openalex.org/W4210480765","https://openalex.org/W4293412117","https://openalex.org/W6717697761","https://openalex.org/W6720006811","https://openalex.org/W6735236233","https://openalex.org/W6748555532","https://openalex.org/W6780742564"],"related_works":["https://openalex.org/W4214877189","https://openalex.org/W2074502265","https://openalex.org/W2773965352","https://openalex.org/W2381179799","https://openalex.org/W2334685461","https://openalex.org/W2366718574","https://openalex.org/W2359774528","https://openalex.org/W3193920202","https://openalex.org/W4318813552","https://openalex.org/W2576964996"],"abstract_inverted_index":{"Device-free":[0],"wireless":[1],"indoor":[2],"localization":[3,76],"is":[4,26],"an":[5],"essential":[6],"technology":[7],"for":[8,75],"the":[9,49,69,105],"Internet":[10],"of":[11,45,57],"Things":[12],"(IoT),":[13],"and":[14,29,52,72,94],"fingerprint-based":[15,24],"methods":[16,25],"are":[17],"widely":[18],"used.":[19],"A":[20],"common":[21],"challenge":[22],"to":[23,111],"data":[27,47,60,70],"collection":[28,71],"labeling.":[30],"This":[31],"paper":[32],"proposes":[33],"a":[34,42,54,112],"few-shot":[35,91],"transfer":[36,92],"learning":[37,93],"system":[38,107],"that":[39,104],"uses":[40],"only":[41],"small":[43],"amount":[44,56],"labeled":[46,59,122],"from":[48],"current":[50],"environment":[51],"reuses":[53],"large":[55],"existing":[58],"previously":[61],"collected":[62],"in":[63,77,85],"other":[64],"environments,":[65],"thereby":[66],"significantly":[67],"reducing":[68],"labeling":[73],"cost":[74],"each":[78],"new":[79],"environment.":[80],"The":[81],"core":[82],"method":[83],"lies":[84],"graph":[86],"neural":[87,114],"network":[88,115],"(GNN)":[89],"based":[90],"its":[95],"modifications.":[96],"Experimental":[97],"results":[98],"conducted":[99],"on":[100],"real-world":[101],"environments":[102],"show":[103],"proposed":[106],"achieves":[108],"comparable":[109],"performance":[110],"convolutional":[113],"(CNN)":[116],"model,":[117],"with":[118],"40":[119],"times":[120],"fewer":[121],"data.":[123]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":7}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}