{"id":"https://openalex.org/W4405271857","doi":"https://doi.org/10.1109/icceic64099.2024.10775532","title":"Combining Transfer Learning and GAN for GPR Target Detection","display_name":"Combining Transfer Learning and GAN for GPR Target Detection","publication_year":2024,"publication_date":"2024-10-11","ids":{"openalex":"https://openalex.org/W4405271857","doi":"https://doi.org/10.1109/icceic64099.2024.10775532"},"language":"en","primary_location":{"id":"doi:10.1109/icceic64099.2024.10775532","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icceic64099.2024.10775532","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 5th International Conference on Computer Engineering and Intelligent Control (ICCEIC)","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/A5046293241","display_name":"Zhongyu Hu","orcid":"https://orcid.org/0000-0002-0748-0954"},"institutions":[{"id":"https://openalex.org/I4387153915","display_name":"Guilin University","ror":"https://ror.org/00jbpxw47","country_code":null,"type":"education","lineage":["https://openalex.org/I4387153915"]},{"id":"https://openalex.org/I5343935","display_name":"Guilin University of Electronic Technology","ror":"https://ror.org/05arjae42","country_code":"CN","type":"education","lineage":["https://openalex.org/I5343935"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhongyu Hu","raw_affiliation_strings":["School of Information and Communication, Guilin University of Electronic Science and Technology,Guilin,China"],"affiliations":[{"raw_affiliation_string":"School of Information and Communication, Guilin University of Electronic Science and Technology,Guilin,China","institution_ids":["https://openalex.org/I4387153915","https://openalex.org/I5343935"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064439261","display_name":"Qinghua Liu","orcid":"https://orcid.org/0000-0002-1052-775X"},"institutions":[{"id":"https://openalex.org/I5343935","display_name":"Guilin University of Electronic Technology","ror":"https://ror.org/05arjae42","country_code":"CN","type":"education","lineage":["https://openalex.org/I5343935"]},{"id":"https://openalex.org/I4387153915","display_name":"Guilin University","ror":"https://ror.org/00jbpxw47","country_code":null,"type":"education","lineage":["https://openalex.org/I4387153915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qinghua Liu","raw_affiliation_strings":["School of Information and Communication, Guilin University of Electronic Science and Technology,Guilin,China"],"affiliations":[{"raw_affiliation_string":"School of Information and Communication, Guilin University of Electronic Science and Technology,Guilin,China","institution_ids":["https://openalex.org/I4387153915","https://openalex.org/I5343935"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5046293241"],"corresponding_institution_ids":["https://openalex.org/I4387153915","https://openalex.org/I5343935"],"apc_list":null,"apc_paid":null,"fwci":0.3554,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.62936195,"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":"12","last_page":"16"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11609","display_name":"Geophysical Methods and Applications","score":0.9994000196456909,"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":0.9994000196456909,"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/T10271","display_name":"Seismic Imaging and Inversion Techniques","score":0.9610000252723694,"subfield":{"id":"https://openalex.org/subfields/1908","display_name":"Geophysics"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11739","display_name":"Microwave Imaging and Scattering Analysis","score":0.9071000218391418,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/ground-penetrating-radar","display_name":"Ground-penetrating radar","score":0.7526406049728394},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.6435290575027466},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5964138507843018},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.34742188453674316},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3305091857910156},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.1737893521785736},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.15367227792739868},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.1381186842918396}],"concepts":[{"id":"https://openalex.org/C71813955","wikidata":"https://www.wikidata.org/wiki/Q503560","display_name":"Ground-penetrating radar","level":3,"score":0.7526406049728394},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.6435290575027466},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5964138507843018},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.34742188453674316},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3305091857910156},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.1737893521785736},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.15367227792739868},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.1381186842918396}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icceic64099.2024.10775532","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icceic64099.2024.10775532","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 5th International Conference on Computer Engineering and Intelligent Control (ICCEIC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","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"],"abstract_inverted_index":{"Using":[0],"transfer":[1,54,94,143,169],"learning":[2,55,89,170],"to":[3,63,72,93,104,130,135,176],"address":[4],"the":[5,8,32,78,95,100,105,125,133,140,145,154,159,179],"issue":[6],"of":[7,10,34,80,111,142,158,165],"difficulties":[9],"obtaining":[11],"real":[12],"samples":[13],"for":[14],"Ground":[15],"penetrating":[16],"radar":[17],"(GPR)":[18],"involves":[19],"a":[20,49,65,86,119,148],"significant":[21],"challenge:":[22],"finding":[23],"an":[24],"appropriate":[25],"pre-training":[26,43,82],"dataset.":[27,108,162],"Current":[28],"approaches":[29],"either":[30],"overlook":[31],"significance":[33],"dataset":[35,67,137],"similarity":[36,138,149],"or":[37],"have":[38],"numerous":[39],"drawbacks":[40],"when":[41],"gathering":[42],"datasets.":[44,83],"To":[45],"overcome":[46],"this":[47],"issue,":[48],"GAN":[50,62,167],"(Generative":[51],"Adversarial":[52],"Network)-based":[53],"approach":[56],"is":[57,69,91,171],"proposed.":[58],"The":[59,109,163],"method":[60,90],"uses":[61],"produce":[64],"simulated":[66,101,160],"that":[68],"very":[70],"comparable":[71],"genuine":[73],"GPR":[74,102,107,161,181],"data,":[75],"effectively":[76],"overcoming":[77],"difficulty":[79],"acquiring":[81],"Following":[84],"that,":[85],"two-stage":[87],"migration":[88],"utilized":[92],"shared":[96],"parameters":[97],"learned":[98],"from":[99],"data":[103],"actual":[106],"accuracy":[110],"target":[112,182],"recognition":[113,183],"was":[114],"further":[115],"increased":[116],"by":[117],"incorporating":[118],"residual":[120],"convolutional":[121],"neural":[122],"network":[123],"into":[124],"feature":[126],"extraction":[127],"network.":[128],"Furthermore,":[129],"thoroughly":[131],"investigate":[132],"extent":[134],"which":[136],"influences":[139],"impact":[141],"learning,":[144],"study":[146],"built":[147],"comparison":[150,174],"model":[151],"and":[152,156,168],"confirmed":[153],"efficacy":[155],"caliber":[157],"technique":[164],"combining":[166],"demonstrated":[172],"through":[173],"studies":[175],"successfully":[177],"raise":[178],"small-sample":[180],"accuracy.":[184]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-12-21T23:12:01.093139","created_date":"2025-10-10T00:00:00"}
