{"id":"https://openalex.org/W7123514100","doi":"https://doi.org/10.1109/access.2026.3653842","title":"Joint Deep Learning for Simultaneous Clutter Removal and Buried Object Detection in GPR","display_name":"Joint Deep Learning for Simultaneous Clutter Removal and Buried Object Detection in GPR","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7123514100","doi":"https://doi.org/10.1109/access.2026.3653842"},"language":null,"primary_location":{"id":"doi:10.1109/access.2026.3653842","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3653842","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2026.3653842","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5095093314","display_name":"Yavuz Emre Kayacan","orcid":"https://orcid.org/0000-0002-8951-1266"},"institutions":[{"id":"https://openalex.org/I48912391","display_name":"Istanbul Technical University","ror":"https://ror.org/059636586","country_code":"TR","type":"education","lineage":["https://openalex.org/I48912391"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Yavuz Emre Kayacan","raw_affiliation_strings":["Department of Electronics and Communication Engineering, Istanbul Technical University, Istanbul, T&#x00FC;rkiye"],"raw_orcid":"https://orcid.org/0000-0002-8951-1266","affiliations":[{"raw_affiliation_string":"Department of Electronics and Communication Engineering, Istanbul Technical University, Istanbul, T&#x00FC;rkiye","institution_ids":["https://openalex.org/I48912391"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010587629","display_name":"I. Erer","orcid":null},"institutions":[{"id":"https://openalex.org/I48912391","display_name":"Istanbul Technical University","ror":"https://ror.org/059636586","country_code":"TR","type":"education","lineage":["https://openalex.org/I48912391"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Isin Erer","raw_affiliation_strings":["Department of Electronics and Communication Engineering, Istanbul Technical University, Istanbul, T&#x00FC;rkiye"],"raw_orcid":"https://orcid.org/0000-0002-2225-6379","affiliations":[{"raw_affiliation_string":"Department of Electronics and Communication Engineering, Istanbul Technical University, Istanbul, T&#x00FC;rkiye","institution_ids":["https://openalex.org/I48912391"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007648588","display_name":"Sel\u00e7uk Paker","orcid":"https://orcid.org/0000-0002-1769-1835"},"institutions":[{"id":"https://openalex.org/I1301968116","display_name":"MEF University","ror":"https://ror.org/05jz51y94","country_code":"TR","type":"education","lineage":["https://openalex.org/I1301968116"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Selcuk Paker","raw_affiliation_strings":["Department of Electrical and Electronics Engineering, Istanbul Ni&#x015F;anta&#x015F;&#x0131; University, Istanbul, T&#x00FC;rkiye"],"raw_orcid":"https://orcid.org/0000-0002-1769-1835","affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronics Engineering, Istanbul Ni&#x015F;anta&#x015F;&#x0131; University, Istanbul, T&#x00FC;rkiye","institution_ids":["https://openalex.org/I1301968116"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.04978701,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"14","issue":null,"first_page":"12240","last_page":"12254"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11609","display_name":"Geophysical Methods and Applications","score":0.977400004863739,"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":0.977400004863739,"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/T11739","display_name":"Microwave Imaging and Scattering Analysis","score":0.01549999974668026,"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"}},{"id":"https://openalex.org/T11312","display_name":"Soil Moisture and Remote Sensing","score":0.0010999999940395355,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/clutter","display_name":"Clutter","score":0.8446999788284302},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.6777999997138977},{"id":"https://openalex.org/keywords/ground-penetrating-radar","display_name":"Ground-penetrating radar","score":0.6313999891281128},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6209999918937683},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.5157999992370605},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4668999910354614},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.46129998564720154},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4577000141143799},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.45089998841285706}],"concepts":[{"id":"https://openalex.org/C132094186","wikidata":"https://www.wikidata.org/wiki/Q641585","display_name":"Clutter","level":3,"score":0.8446999788284302},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7818999886512756},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.72079998254776},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.6777999997138977},{"id":"https://openalex.org/C71813955","wikidata":"https://www.wikidata.org/wiki/Q503560","display_name":"Ground-penetrating radar","level":3,"score":0.6313999891281128},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6209999918937683},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.5157999992370605},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4668999910354614},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.46129998564720154},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4577000141143799},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.45320001244544983},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.45089998841285706},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.44929999113082886},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.4074999988079071},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.40230000019073486},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.35040000081062317},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.334199994802475},{"id":"https://openalex.org/C10929652","wikidata":"https://www.wikidata.org/wiki/Q7279985","display_name":"Radar imaging","level":3,"score":0.32919999957084656},{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.32679998874664307},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.32260000705718994},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.31459999084472656},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.3091000020503998},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.30570000410079956},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.3034000098705292},{"id":"https://openalex.org/C193415008","wikidata":"https://www.wikidata.org/wiki/Q639681","display_name":"Network architecture","level":2,"score":0.29600000381469727},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.2919999957084656},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2759999930858612},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.2711000144481659},{"id":"https://openalex.org/C32283439","wikidata":"https://www.wikidata.org/wiki/Q1407014","display_name":"Radar tracker","level":3,"score":0.2605000138282776}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2026.3653842","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3653842","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:polen.itu.edu.tr:11527/75034","is_oa":false,"landing_page_url":"https://hdl.handle.net/11527/75034","pdf_url":null,"source":{"id":"https://openalex.org/S4306400460","display_name":"Istanbul Technical University Academic Open Archive (Istanbul Technical University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I48912391","host_organization_name":"Istanbul Technical University","host_organization_lineage":["https://openalex.org/I48912391"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"}],"best_oa_location":{"id":"doi:10.1109/access.2026.3653842","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3653842","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.4345802962779999,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"},{"score":0.427184134721756,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G101748119","display_name":null,"funder_award_id":"MGA-2025-46531","funder_id":"https://openalex.org/F4320336848","funder_display_name":"Bilimsel Ara\u015ft\u0131rma Projeleri Birimi, \u0130stanbul Teknik \u00dcniversitesi"},{"id":"https://openalex.org/G8877696087","display_name":null,"funder_award_id":"120E234","funder_id":"https://openalex.org/F4320322626","funder_display_name":"T\u00fcrkiye Bilimsel ve Teknolojik Ara\u015ft\u0131rma Kurumu"}],"funders":[{"id":"https://openalex.org/F4320322626","display_name":"T\u00fcrkiye Bilimsel ve Teknolojik Ara\u015ft\u0131rma Kurumu","ror":"https://ror.org/04w9kkr77"},{"id":"https://openalex.org/F4320336848","display_name":"Bilimsel Ara\u015ft\u0131rma Projeleri Birimi, \u0130stanbul Teknik \u00dcniversitesi","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W1998239584","https://openalex.org/W2032399238","https://openalex.org/W2528186534","https://openalex.org/W2536196763","https://openalex.org/W2728294189","https://openalex.org/W2774603543","https://openalex.org/W2909269180","https://openalex.org/W2963249133","https://openalex.org/W2972774735","https://openalex.org/W3009058813","https://openalex.org/W3016990741","https://openalex.org/W3098645781","https://openalex.org/W3119622082","https://openalex.org/W3185315065","https://openalex.org/W3207003426","https://openalex.org/W4226458280","https://openalex.org/W4280551717","https://openalex.org/W4285253033","https://openalex.org/W4303183155","https://openalex.org/W4323065917","https://openalex.org/W4327785494","https://openalex.org/W4328029475","https://openalex.org/W4376456507","https://openalex.org/W4377232672","https://openalex.org/W4378379053","https://openalex.org/W4392910810","https://openalex.org/W4394002349","https://openalex.org/W4398775870","https://openalex.org/W4399416280","https://openalex.org/W4400579363","https://openalex.org/W4400722392","https://openalex.org/W4402125981","https://openalex.org/W4403022803","https://openalex.org/W4403759087","https://openalex.org/W4404708486","https://openalex.org/W4404809442","https://openalex.org/W4409613257"],"related_works":[],"abstract_inverted_index":{"Ground":[0],"Penetrating":[1],"Radar":[2],"(GPR)":[3],"data":[4,185],"presents":[5,40],"a":[6,80,107],"challenging":[7,165,214],"problem":[8],"for":[9,224],"detecting":[10],"subsurface":[11],"targets":[12,171],"due":[13],"to":[14,87,140,180],"surface":[15],"reflections":[16],"and":[17,32,133,172,186,209],"the":[18,52,56,58,77,94,98,116,131,141,146,150,177,194],"complex":[19],"clutter":[20,30,70],"caused":[21],"by":[22,175,221],"heterogeneous":[23],"soil":[24],"structures.":[25],"While":[26],"traditional":[27],"methods":[28],"treat":[29],"removal":[31,71],"target":[33],"detection":[34,81,84,178],"as":[35,168],"separate":[36],"processes,":[37],"this":[38,92,124],"study":[39],"an":[41,210],"integrated":[42],"deep":[43],"learning":[44],"approach":[45],"that":[46,66,112,127,193],"simultaneously":[47],"optimizes":[48],"both":[49,182],"tasks.":[50],"In":[51],"first":[53,59],"phase":[54,96],"of":[55,69,123,145],"study,":[57],"proposed":[60,151,195],"model,":[61],"Dec-YOLO":[62],"(Model":[63,101],"I),":[64],"demonstrated":[65],"\u201cjoint":[67],"training\u201d":[68],"networks":[72],"(UNet,":[73],"CR-Net,":[74],"DC-ViT)":[75],"from":[76,115],"literature":[78],"with":[79],"network":[82,179],"improves":[83],"performance":[85],"compared":[86],"sequential":[88],"methods.":[89],"Building":[90],"on":[91,206],"finding,":[93],"second":[95],"proposes":[97],"original":[99],"RAFDeC-YOLO":[100],"II)":[102],"architecture.":[103],"This":[104,156],"architecture":[105,148],"features":[106],"specialized":[108],"denoising":[109],"block":[110],"(decoder)":[111],"branches":[113],"off":[114],"standard":[117],"YOLOv12":[118],"backbone.":[119],"The":[120],"fundamental":[121],"innovation":[122],"branch":[125],"is":[126],"it":[128,137],"feeds":[129],"back":[130,139],"cleaned":[132,187],"enriched":[134],"feature":[135,158],"maps":[136],"produces":[138],"relevant":[142],"neck":[143],"layers":[144],"YOLO":[147],"via":[149],"Residual":[152],"Adapter":[153],"Fusion":[154],"mechanism.":[155],"strategic":[157],"transfer":[159],"maximizes":[160],"discriminative":[161],"power,":[162],"particularly":[163],"in":[164,213],"scenarios":[166],"such":[167],"weak":[169],"dielectric":[170],"asphalt-covered":[173],"surfaces,":[174],"enabling":[176],"access":[181],"noisy":[183],"raw":[184],"spatial":[188],"details.":[189],"Experimental":[190],"results":[191],"demonstrate":[192],"framework":[196],"outperforms":[197],"state-of-the-art":[198],"methods,":[199],"achieving":[200],"over":[201],"25.8%":[202],"higher":[203],"localization":[204],"accuracy":[205],"hybrid":[207],"datasets":[208],"87.5%":[211],"improvement":[212],"real-world":[215],"scenarios,":[216],"while":[217],"reducing":[218],"computational":[219],"complexity":[220],"approximately":[222],"43%":[223],"efficient":[225],"deployment.":[226]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-01-14T00:00:00"}
