{"id":"https://openalex.org/W2884209645","doi":"https://doi.org/10.1109/vtcspring.2018.8417850","title":"Heterogeneous Feature Machine Learning for Performance-Enhancing Indoor Localization","display_name":"Heterogeneous Feature Machine Learning for Performance-Enhancing Indoor Localization","publication_year":2018,"publication_date":"2018-06-01","ids":{"openalex":"https://openalex.org/W2884209645","doi":"https://doi.org/10.1109/vtcspring.2018.8417850","mag":"2884209645"},"language":"en","primary_location":{"id":"doi:10.1109/vtcspring.2018.8417850","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vtcspring.2018.8417850","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE 87th Vehicular Technology Conference (VTC Spring)","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/A5035103594","display_name":"Lingwen Zhang","orcid":"https://orcid.org/0000-0001-7661-6547"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Lingwen Zhang","raw_affiliation_strings":["Beijing Jiaotong University, Beijing, Beijing, CN"],"affiliations":[{"raw_affiliation_string":"Beijing Jiaotong University, Beijing, Beijing, CN","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102016693","display_name":"Ning Xiao","orcid":"https://orcid.org/0000-0003-0652-0819"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ning Xiao","raw_affiliation_strings":["Beijing Jiaotong University, Beijing, Beijing, CN"],"affiliations":[{"raw_affiliation_string":"Beijing Jiaotong University, Beijing, Beijing, CN","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100361949","display_name":"Jun Li","orcid":"https://orcid.org/0000-0002-8059-2821"},"institutions":[{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jun Li","raw_affiliation_strings":["New York University, New York, NY, US"],"affiliations":[{"raw_affiliation_string":"New York University, New York, NY, US","institution_ids":["https://openalex.org/I57206974"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100748705","display_name":"Wenkao Yang","orcid":"https://orcid.org/0000-0002-4524-8574"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenkao Yang","raw_affiliation_strings":["School of Electrical and Computer Engineering, Beijing Jiaotong University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5035103594"],"corresponding_institution_ids":["https://openalex.org/I21193070"],"apc_list":null,"apc_paid":null,"fwci":0.2575,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.56504533,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"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/T10860","display_name":"Speech and Audio Processing","score":0.9933000206947327,"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9873999953269958,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/robustness","display_name":"Robustness (evolution)","score":0.9187345504760742},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7605258226394653},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.632466197013855},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5483487248420715},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5361708402633667},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.44289225339889526},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.33292263746261597}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.9187345504760742},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7605258226394653},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.632466197013855},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5483487248420715},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5361708402633667},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44289225339889526},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.33292263746261597},{"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},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","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/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/vtcspring.2018.8417850","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vtcspring.2018.8417850","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE 87th Vehicular Technology Conference (VTC Spring)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1591182554","https://openalex.org/W1889684668","https://openalex.org/W1960384938","https://openalex.org/W1964083272","https://openalex.org/W1965006965","https://openalex.org/W2036998483","https://openalex.org/W2053254995","https://openalex.org/W2053820106","https://openalex.org/W2053834050","https://openalex.org/W2133874683","https://openalex.org/W2156909104","https://openalex.org/W2165180969","https://openalex.org/W2166781916","https://openalex.org/W2171878866","https://openalex.org/W2202721006","https://openalex.org/W2221380621","https://openalex.org/W2398544875","https://openalex.org/W2549315536","https://openalex.org/W2739026601","https://openalex.org/W4206686222","https://openalex.org/W4234020819"],"related_works":["https://openalex.org/W2378211422","https://openalex.org/W4321353415","https://openalex.org/W2745001401","https://openalex.org/W2130974462","https://openalex.org/W2028665553","https://openalex.org/W2086519370","https://openalex.org/W972276598","https://openalex.org/W4246352526","https://openalex.org/W2121910908","https://openalex.org/W2951187577"],"abstract_inverted_index":{"Currently":[0],"there":[1],"is":[2,29,48],"a":[3],"trend":[4],"in":[5],"indoor":[6,62],"localization":[7],"by":[8,70],"utilizing":[9],"machine":[10,23],"learning.":[11],"However,":[12],"the":[13,35,57],"precision":[14,58],"and":[15,39,59,66],"robustness":[16,60],"are":[17,68],"limited":[18],"due":[19],"to":[20,41,49,55],"single":[21,31],"feature":[22,32],"learning":[24],"scheme.":[25],"The":[26,43],"reason":[27],"behind":[28],"that":[30],"cannot":[33],"capture":[34],"complete":[36],"channel":[37],"characteristics":[38],"susceptible":[40],"interference.":[42],"objective":[44],"of":[45,61],"this":[46],"paper":[47],"introduce":[50],"heterogeneous":[51],"features":[52],"fusion":[53],"model":[54],"enhance":[56],"positioning.":[63],"Its":[64],"effectiveness":[65],"efficiency":[67],"proved":[69],"comparing":[71],"with":[72],"current":[73],"benchmark.":[74]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-25T21:42:39.735039","created_date":"2025-10-10T00:00:00"}
