{"id":"https://openalex.org/W4400944470","doi":"https://doi.org/10.1109/tgrs.2024.3432933","title":"Indicator-Guided Multifrequency GPR Data Fusion With Transformer","display_name":"Indicator-Guided Multifrequency GPR Data Fusion With Transformer","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4400944470","doi":"https://doi.org/10.1109/tgrs.2024.3432933"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2024.3432933","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2024.3432933","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"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 Geoscience and Remote Sensing","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/A5072808087","display_name":"Shufan Hu","orcid":"https://orcid.org/0000-0002-2499-5511"},"institutions":[{"id":"https://openalex.org/I141649914","display_name":"Nanchang University","ror":"https://ror.org/042v6xz23","country_code":"CN","type":"education","lineage":["https://openalex.org/I141649914"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shufan Hu","raw_affiliation_strings":["School of Mathematics and Computer Sciences, Nanchang University, Nanchang, China"],"raw_orcid":"https://orcid.org/0000-0002-2499-5511","affiliations":[{"raw_affiliation_string":"School of Mathematics and Computer Sciences, Nanchang University, Nanchang, China","institution_ids":["https://openalex.org/I141649914"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084445506","display_name":"Huilin Zhou","orcid":"https://orcid.org/0000-0002-5350-0012"},"institutions":[{"id":"https://openalex.org/I141649914","display_name":"Nanchang University","ror":"https://ror.org/042v6xz23","country_code":"CN","type":"education","lineage":["https://openalex.org/I141649914"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huilin Zhou","raw_affiliation_strings":["School of Information Engineering, Nanchang University, Nanchang, China"],"raw_orcid":"https://orcid.org/0000-0002-5350-0012","affiliations":[{"raw_affiliation_string":"School of Information Engineering, Nanchang University, Nanchang, China","institution_ids":["https://openalex.org/I141649914"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100458084","display_name":"Yonghui Zhao","orcid":"https://orcid.org/0000-0002-8120-6435"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yonghui Zhao","raw_affiliation_strings":["School of Ocean and Earth Science, Tongji University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-8120-6435","affiliations":[{"raw_affiliation_string":"School of Ocean and Earth Science, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101699398","display_name":"Wei Cai","orcid":"https://orcid.org/0000-0002-9340-8501"},"institutions":[{"id":"https://openalex.org/I141649914","display_name":"Nanchang University","ror":"https://ror.org/042v6xz23","country_code":"CN","type":"education","lineage":["https://openalex.org/I141649914"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Cai","raw_affiliation_strings":["School of Mathematics and Computer Sciences, Nanchang University, Nanchang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematics and Computer Sciences, Nanchang University, Nanchang, China","institution_ids":["https://openalex.org/I141649914"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036073535","display_name":"Kunwei Feng","orcid":null},"institutions":[{"id":"https://openalex.org/I4210150300","display_name":"Guzhou Transportation Planning Survey & Design Academe (China)","ror":"https://ror.org/048yeyk79","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210150300"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kunwei Feng","raw_affiliation_strings":["Guizhou Transportation Planning Survey &#x0026; Design Academe Company Ltd., Guiyang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guizhou Transportation Planning Survey &#x0026; Design Academe Company Ltd., Guiyang, China","institution_ids":["https://openalex.org/I4210150300"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.1812,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.7669874,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"62","issue":null,"first_page":"1","last_page":"13"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11609","display_name":"Geophysical Methods and Applications","score":0.9932000041007996,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean 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/T11609","display_name":"Geophysical Methods and Applications","score":0.9932000041007996,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean 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/T14339","display_name":"Image Processing and 3D Reconstruction","score":0.9688000082969666,"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"}},{"id":"https://openalex.org/T14392","display_name":"Geoscience and Mining Technology","score":0.9456999897956848,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"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/ground-penetrating-radar","display_name":"Ground-penetrating radar","score":0.7923455238342285},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.5203844308853149},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.5140934586524963},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.4822283685207367},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.40368348360061646},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.2634187936782837},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2034429907798767}],"concepts":[{"id":"https://openalex.org/C71813955","wikidata":"https://www.wikidata.org/wiki/Q503560","display_name":"Ground-penetrating radar","level":3,"score":0.7923455238342285},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.5203844308853149},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.5140934586524963},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.4822283685207367},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.40368348360061646},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.2634187936782837},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2034429907798767},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2024.3432933","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2024.3432933","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"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 Geoscience and Remote Sensing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","score":0.6600000262260437,"display_name":"Affordable and clean energy"}],"awards":[{"id":"https://openalex.org/G698499258","display_name":null,"funder_award_id":"20232BAB212005","funder_id":"https://openalex.org/F4320322665","funder_display_name":"Natural Science Foundation of Jiangxi Province"},{"id":"https://openalex.org/G8099022390","display_name":null,"funder_award_id":"42304158","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"},{"id":"https://openalex.org/F4320322665","display_name":"Natural Science Foundation of Jiangxi Province","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W1986754283","https://openalex.org/W2003597489","https://openalex.org/W2013301680","https://openalex.org/W2079393981","https://openalex.org/W2089141316","https://openalex.org/W2313224414","https://openalex.org/W2325984875","https://openalex.org/W2518909974","https://openalex.org/W2759758570","https://openalex.org/W2772143815","https://openalex.org/W2786410487","https://openalex.org/W2803071093","https://openalex.org/W2917480588","https://openalex.org/W3003226679","https://openalex.org/W3021118108","https://openalex.org/W3163993681","https://openalex.org/W3179950556","https://openalex.org/W3181367324","https://openalex.org/W3185007799","https://openalex.org/W3214556222","https://openalex.org/W4309828240","https://openalex.org/W4379233577","https://openalex.org/W4385245566","https://openalex.org/W4386859756","https://openalex.org/W4392405501","https://openalex.org/W6631943919","https://openalex.org/W6638545294","https://openalex.org/W6730183235"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W4315471419","https://openalex.org/W2946057701","https://openalex.org/W4386931161","https://openalex.org/W2374146176","https://openalex.org/W2065249286","https://openalex.org/W2366839571","https://openalex.org/W4223960160","https://openalex.org/W2027762722"],"abstract_inverted_index":{"Multifrequency":[0],"ground":[1],"penetrating":[2],"radar":[3],"(GPR)":[4],"data":[5,39,68,84,115,142,175,217],"fusion":[6,40,50,56,61,88,155,166,205],"integrates":[7],"complementary":[8],"information":[9,128,172],"from":[10,173,180],"multiple":[11],"single":[12,81],"central":[13,82,113],"frequency":[14,83,114],"measurements":[15],"into":[16],"a":[17,186,193,211],"composite":[18],"radargram,":[19],"broadening":[20],"the":[21,43,49,55,60,70,77,93,103,109,121,132,147,157],"spectral":[22],"bandwidth":[23],"of":[24,47,63,73,111,137,214],"signals":[25,179],"and":[26,30,85,140,163],"improving":[27],"interpretation":[28],"efficiency":[29,162],"accuracy.":[31],"Here,":[32],"we":[33,53,99],"develop":[34],"an":[35,200],"indicator-guided":[36],"multifrequency":[37,66,203,215],"GPR":[38,67,95,204,216],"algorithm":[41,159],"with":[42,69,146,192],"transformer":[44],"network.":[45],"Instead":[46],"generating":[48],"result":[51],"directly,":[52],"design":[54],"network":[57,122,153],"to":[58,75,123,223],"integrate":[59],"process":[62],"combining":[64],"original":[65],"main":[71],"idea":[72],"learning":[74],"understand":[76],"difference":[78],"between":[79],"different":[80,117],"then":[86],"producing":[87],"weights,":[89],"ultimately":[90],"resulting":[91],"in":[92,131],"fused":[94],"data.":[96,182],"The":[97,135],"indicator":[98],"used,":[100],"which":[101],"is":[102],"1-D":[104],"Laplacian":[105],"operator":[106],"gradient":[107],"representing":[108],"importance":[110],"each":[112],"at":[116],"time":[118],"windows,":[119],"guides":[120],"preserve":[124],"as":[125,129],"much":[126],"high-resolution":[127,171],"possible":[130],"overlapping":[133],"area.":[134],"results":[136,167],"synthetic,":[138],"experimental,":[139],"field":[141],"indicate":[143],"that,":[144],"compared":[145],"recently":[148],"developed":[149],"long":[150],"short-term":[151],"memory":[152],"(LSTM)-based":[154],"algorithm,":[156],"proposed":[158],"shows":[160],"high":[161],"provides":[164,199],"better":[165],"that":[168],"retain":[169],"more":[170],"high-frequency":[174],"without":[176],"losing":[177],"deep":[178],"low-frequency":[181],"Moreover,":[183],"it":[184,198],"presents":[185],"good":[187],"generalization":[188],"capability":[189],"for":[190,208],"datasets":[191],"similar":[194,220],"acquisition":[195],"situation.":[196],"Therefore,":[197],"effective":[201],"real-time":[202],"solution,":[206],"especially":[207],"cases":[209],"where":[210],"large":[212],"amount":[213],"measured":[218],"under":[219],"circumstances":[221],"needs":[222],"be":[224],"fused.":[225]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
