{"id":"https://openalex.org/W4415524326","doi":"https://doi.org/10.1109/mlsp62443.2025.11204298","title":"IRM-Net: An Enhanced Attention Networks for Indoor Radio Map Estimation","display_name":"IRM-Net: An Enhanced Attention Networks for Indoor Radio Map Estimation","publication_year":2025,"publication_date":"2025-08-31","ids":{"openalex":"https://openalex.org/W4415524326","doi":"https://doi.org/10.1109/mlsp62443.2025.11204298"},"language":null,"primary_location":{"id":"doi:10.1109/mlsp62443.2025.11204298","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mlsp62443.2025.11204298","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 35th International Workshop on Machine Learning for Signal Processing (MLSP)","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/A5114244996","display_name":"Qi Chen","orcid":"https://orcid.org/0009-0001-8207-5406"},"institutions":[{"id":"https://openalex.org/I189210763","display_name":"Yunnan University","ror":"https://ror.org/0040axw97","country_code":"CN","type":"education","lineage":["https://openalex.org/I189210763"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Qi Chen","raw_affiliation_strings":["Yunnan University,School of Information Science and Engineering,Kunming,China,650500"],"affiliations":[{"raw_affiliation_string":"Yunnan University,School of Information Science and Engineering,Kunming,China,650500","institution_ids":["https://openalex.org/I189210763"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Haidong Tan","orcid":null},"institutions":[{"id":"https://openalex.org/I189210763","display_name":"Yunnan University","ror":"https://ror.org/0040axw97","country_code":"CN","type":"education","lineage":["https://openalex.org/I189210763"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haidong Tan","raw_affiliation_strings":["Yunnan University,School of Information Science and Engineering,Kunming,China,650500"],"affiliations":[{"raw_affiliation_string":"Yunnan University,School of Information Science and Engineering,Kunming,China,650500","institution_ids":["https://openalex.org/I189210763"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063439671","display_name":"Jingjing Yang","orcid":"https://orcid.org/0000-0003-2751-2930"},"institutions":[{"id":"https://openalex.org/I189210763","display_name":"Yunnan University","ror":"https://ror.org/0040axw97","country_code":"CN","type":"education","lineage":["https://openalex.org/I189210763"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingjing Yang","raw_affiliation_strings":["Yunnan University,School of Information Science and Engineering,Kunming,China,650500"],"affiliations":[{"raw_affiliation_string":"Yunnan University,School of Information Science and Engineering,Kunming,China,650500","institution_ids":["https://openalex.org/I189210763"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004290542","display_name":"Ming Huang","orcid":"https://orcid.org/0000-0002-9517-2125"},"institutions":[{"id":"https://openalex.org/I189210763","display_name":"Yunnan University","ror":"https://ror.org/0040axw97","country_code":"CN","type":"education","lineage":["https://openalex.org/I189210763"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ming Huang","raw_affiliation_strings":["Yunnan University,School of Information Science and Engineering,Kunming,China,650500"],"affiliations":[{"raw_affiliation_string":"Yunnan University,School of Information Science and Engineering,Kunming,China,650500","institution_ids":["https://openalex.org/I189210763"]}]},{"author_position":"last","author":{"id":null,"display_name":"Boyuan Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I189210763","display_name":"Yunnan University","ror":"https://ror.org/0040axw97","country_code":"CN","type":"education","lineage":["https://openalex.org/I189210763"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Boyuan Chen","raw_affiliation_strings":["Yunnan University,School of Information Science and Engineering,Kunming,China,650500"],"affiliations":[{"raw_affiliation_string":"Yunnan University,School of Information Science and Engineering,Kunming,China,650500","institution_ids":["https://openalex.org/I189210763"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5114244996"],"corresponding_institution_ids":["https://openalex.org/I189210763"],"apc_list":null,"apc_paid":null,"fwci":1.3546,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.85413788,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9962999820709229,"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"}},"topics":[{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9962999820709229,"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/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9904999732971191,"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/T10901","display_name":"Advanced Data Compression Techniques","score":0.9726999998092651,"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/block","display_name":"Block (permutation group theory)","score":0.6923999786376953},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6532999873161316},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.6330999732017517},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4652000069618225},{"id":"https://openalex.org/keywords/path-loss","display_name":"Path loss","score":0.4390000104904175},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.43869999051094055},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3531999886035919},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.3391000032424927}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7907999753952026},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.6923999786376953},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6532999873161316},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.6330999732017517},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.47440001368522644},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4652000069618225},{"id":"https://openalex.org/C194273485","wikidata":"https://www.wikidata.org/wiki/Q1478845","display_name":"Path loss","level":3,"score":0.4390000104904175},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.43869999051094055},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.40470001101493835},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3531999886035919},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3391000032424927},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.3361999988555908},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3257000148296356},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.2939999997615814},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.29120001196861267},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.29019999504089355},{"id":"https://openalex.org/C144559511","wikidata":"https://www.wikidata.org/wiki/Q2986279","display_name":"Principal (computer security)","level":2,"score":0.28349998593330383},{"id":"https://openalex.org/C2988416141","wikidata":"https://www.wikidata.org/wiki/Q6031139","display_name":"Information loss","level":2,"score":0.27970001101493835},{"id":"https://openalex.org/C157899210","wikidata":"https://www.wikidata.org/wiki/Q1395022","display_name":"Convolutional code","level":3,"score":0.2752000093460083},{"id":"https://openalex.org/C193519340","wikidata":"https://www.wikidata.org/wiki/Q891179","display_name":"Data loss","level":2,"score":0.26330000162124634}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/mlsp62443.2025.11204298","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mlsp62443.2025.11204298","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 35th International Workshop on Machine Learning for Signal Processing (MLSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2842479385","display_name":null,"funder_award_id":"62361055,62261059,61963037","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":13,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W2133665775","https://openalex.org/W2884436604","https://openalex.org/W2963073614","https://openalex.org/W3015788359","https://openalex.org/W3025800305","https://openalex.org/W3131967102","https://openalex.org/W3174380871","https://openalex.org/W4289752563","https://openalex.org/W4387885643","https://openalex.org/W4401815593","https://openalex.org/W4404520626","https://openalex.org/W4415524661"],"related_works":[],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,29,61],"introduce":[4],"IRM-Net,":[5],"a":[6,35,39,45],"novel":[7],"variant":[8],"of":[9,38],"the":[10,25,53,67,91,96],"U-Net":[11],"architecture":[12],"designed":[13],"for":[14],"indoor":[15,119],"radio":[16],"map":[17],"estimation.":[18],"IRM-Net":[19,85],"incorporates":[20],"two":[21],"principal":[22],"improvements":[23],"over":[24],"standard":[26],"U-Net.":[27],"First,":[28],"replace":[30],"conventional":[31],"convolutional":[32],"layers":[33],"with":[34],"cascaded":[36],"combination":[37],"Detail":[40,46],"Enhancement":[41,47],"Block":[42,49],"(DEB)":[43],"and":[44,69,88],"Attention":[48],"(DEAB),":[50],"which":[51],"enhances":[52],"model's":[54],"ability":[55],"to":[56],"capture":[57],"finegrained":[58],"features.":[59],"Second,":[60],"implement":[62],"dense":[63],"connections":[64],"in":[65,116],"both":[66],"encoder":[68],"decoder,":[70],"facilitating":[71],"multi-level":[72],"semantic":[73],"interactions":[74],"that":[75,107],"mitigate":[76],"information":[77],"loss":[78,114],"more":[79],"effectively":[80],"than":[81],"traditional":[82],"serial":[83],"connections.":[84],"was":[86],"trained":[87],"evaluated":[89],"on":[90],"benchmark":[92],"dataset":[93],"provided":[94],"by":[95],"Sampling-Assisted":[97],"Pathloss":[98],"Radio":[99],"Map":[100],"Prediction":[101],"Data":[102],"Competition.":[103],"Experimental":[104],"results":[105],"demonstrate":[106],"our":[108],"approach":[109],"can":[110],"reliably":[111],"predict":[112],"path":[113],"distributions":[115],"previously":[117],"unseen":[118],"environments.":[120]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2025-10-24T00:00:00"}
