{"id":"https://openalex.org/W3201980669","doi":"https://doi.org/10.1145/3460418.3480406","title":"Three-Dimensional Indoor Visible Light Localization: A Learning-Based Approach","display_name":"Three-Dimensional Indoor Visible Light Localization: A Learning-Based Approach","publication_year":2021,"publication_date":"2021-09-21","ids":{"openalex":"https://openalex.org/W3201980669","doi":"https://doi.org/10.1145/3460418.3480406","mag":"3201980669"},"language":"en","primary_location":{"id":"doi:10.1145/3460418.3480406","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3460418.3480406","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Adjunct Proceedings of the 2021 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2021 ACM International Symposium on Wearable Computers","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/A5087319572","display_name":"Danping Su","orcid":"https://orcid.org/0000-0003-1951-6966"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Danping Su","raw_affiliation_strings":["Information and Communication Engineering, Xiamen University, China"],"affiliations":[{"raw_affiliation_string":"Information and Communication Engineering, Xiamen University, China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101832799","display_name":"Xianbin Liu","orcid":"https://orcid.org/0000-0001-8441-4435"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xianbin Liu","raw_affiliation_strings":["Department of Information and Communication Engineering, Xiamen University, Xiamen University, China"],"affiliations":[{"raw_affiliation_string":"Department of Information and Communication Engineering, Xiamen University, Xiamen University, China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100684825","display_name":"Sicong Liu","orcid":"https://orcid.org/0000-0002-5710-0446"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sicong Liu","raw_affiliation_strings":["Dept. Information &amp; Communication Engineering, School of Informatics, Xiamen University, China"],"affiliations":[{"raw_affiliation_string":"Dept. Information &amp; Communication Engineering, School of Informatics, Xiamen University, China","institution_ids":["https://openalex.org/I191208505"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5087319572"],"corresponding_institution_ids":["https://openalex.org/I191208505"],"apc_list":null,"apc_paid":null,"fwci":0.6016,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.67188133,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"672","last_page":"677"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10851","display_name":"Optical Wireless Communication Technologies","score":0.9997000098228455,"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/T10851","display_name":"Optical Wireless Communication Technologies","score":0.9997000098228455,"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/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9979000091552734,"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/T11019","display_name":"Image Enhancement Techniques","score":0.9930999875068665,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.6956149339675903},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6945924758911133},{"id":"https://openalex.org/keywords/visible-light-communication","display_name":"Visible light communication","score":0.6886608600616455},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6150804162025452},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.49651771783828735},{"id":"https://openalex.org/keywords/light-emitting-diode","display_name":"Light-emitting diode","score":0.4932226538658142},{"id":"https://openalex.org/keywords/plane","display_name":"Plane (geometry)","score":0.4856773614883423},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.48114216327667236},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.4671708047389984},{"id":"https://openalex.org/keywords/position","display_name":"Position (finance)","score":0.4408324360847473},{"id":"https://openalex.org/keywords/structured-light","display_name":"Structured light","score":0.4206628203392029},{"id":"https://openalex.org/keywords/spatial-reference-system","display_name":"Spatial reference system","score":0.4132035970687866},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3264790177345276},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.3238310217857361},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.19900822639465332},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.16254380345344543},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.12655770778656006}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6956149339675903},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6945924758911133},{"id":"https://openalex.org/C160487672","wikidata":"https://www.wikidata.org/wiki/Q1426313","display_name":"Visible light communication","level":3,"score":0.6886608600616455},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6150804162025452},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.49651771783828735},{"id":"https://openalex.org/C176666156","wikidata":"https://www.wikidata.org/wiki/Q25504","display_name":"Light-emitting diode","level":2,"score":0.4932226538658142},{"id":"https://openalex.org/C17825722","wikidata":"https://www.wikidata.org/wiki/Q17285","display_name":"Plane (geometry)","level":2,"score":0.4856773614883423},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.48114216327667236},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.4671708047389984},{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.4408324360847473},{"id":"https://openalex.org/C193581530","wikidata":"https://www.wikidata.org/wiki/Q683778","display_name":"Structured light","level":2,"score":0.4206628203392029},{"id":"https://openalex.org/C194226119","wikidata":"https://www.wikidata.org/wiki/Q161779","display_name":"Spatial reference system","level":2,"score":0.4132035970687866},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3264790177345276},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.3238310217857361},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19900822639465332},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.16254380345344543},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.12655770778656006},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3460418.3480406","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3460418.3480406","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Adjunct Proceedings of the 2021 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2021 ACM International Symposium on Wearable Computers","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1334407892","display_name":null,"funder_award_id":"61901403","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":25,"referenced_works":["https://openalex.org/W1979370046","https://openalex.org/W2073808079","https://openalex.org/W2193650110","https://openalex.org/W2280661472","https://openalex.org/W2337441051","https://openalex.org/W2526300161","https://openalex.org/W2557283755","https://openalex.org/W2613445145","https://openalex.org/W2769094067","https://openalex.org/W2782130364","https://openalex.org/W2807301232","https://openalex.org/W2808244687","https://openalex.org/W2891700425","https://openalex.org/W2905430872","https://openalex.org/W2911806414","https://openalex.org/W2921530591","https://openalex.org/W2950863887","https://openalex.org/W2963688708","https://openalex.org/W2969465399","https://openalex.org/W2971328001","https://openalex.org/W2999368263","https://openalex.org/W3004277316","https://openalex.org/W3105266807","https://openalex.org/W3139362963","https://openalex.org/W4232533449"],"related_works":["https://openalex.org/W2345184372","https://openalex.org/W3013515612","https://openalex.org/W2136184105","https://openalex.org/W2187500075","https://openalex.org/W2041399278","https://openalex.org/W2360764675","https://openalex.org/W43236265","https://openalex.org/W2160451891","https://openalex.org/W2336974148","https://openalex.org/W2056016498"],"abstract_inverted_index":{"In":[0,87],"this":[1],"paper,":[2],"a":[3,42],"three-dimensional":[4],"(3D)":[5],"indoor":[6,82,155],"visible":[7,83,91,164,173],"light":[8,84,92,165,174],"localization":[9,50,85,93,156,166,175],"method":[10],"based":[11,66],"on":[12,35,127],"machine":[13,45,58],"learning":[14,17,46,65,109],"and":[15,38,59,111,138,182,188],"deep":[16,64,68],"is":[18,21],"presented,":[19],"which":[20],"able":[22],"to":[23,179],"obtain":[24],"accurate":[25,139],"3D":[26,140,154],"spatial":[27,184],"coordinates":[28,115,141],"of":[29,72,99,107,153,171,186,191],"the":[30,33,36,39,63,88,95,105,108,112,119,124,128,134,161,169,172,180,183,189],"user,":[31],"including":[32],"location":[34,126],"plane":[37,129],"height":[40,135,143],"in":[41,80],"room.":[43],"The":[44,146],"approaches":[47],"adopted":[48],"for":[49,78],"include":[51],"two":[52],"typical":[53],"algorithms,":[54],"i.e.,":[55],"support":[56],"vector":[57],"random":[60],"forest.":[61],"For":[62],"approach,":[67],"neural":[69,192],"networks":[70],"composed":[71],"full":[73],"connected":[74],"layers":[75],"are":[76,102,116,144,195],"employed":[77],"training":[79],"different":[81],"scenarios.":[86],"formulated":[89],"learning-based":[90,163],"framework,":[94],"received":[96],"signal":[97],"strength":[98],"light-emitting":[100],"diodes":[101],"taken":[103],"as":[104,118],"input":[106],"algorithm,":[110],"measured":[113],"position":[114],"inferred":[117],"output.":[120],"Apart":[121],"from":[122],"obtaining":[123],"two-dimensional":[125],"accurately,":[130],"we":[131],"also":[132,196],"take":[133],"into":[136],"account":[137],"with":[142,177],"obtained.":[145],"experimental":[147],"results":[148],"show":[149],"that":[150],"centimeter-scale":[151],"accuracy":[152],"can":[157],"be":[158],"achieved":[159],"using":[160],"proposed":[162],"method.":[167],"Moreover,":[168],"performance":[170],"methods":[176],"respect":[178],"number":[181,190],"pattern":[185],"LEDs,":[187],"network":[193],"layers,":[194],"investigated.":[197]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
