{"id":"https://openalex.org/W7134904875","doi":"https://doi.org/10.1109/access.2026.3672644","title":"AWANet: Improved YOLOv11\u2019s Adaptive Weighted Attention Network for Haystack Detection in Airborne SAR Imagery","display_name":"AWANet: Improved YOLOv11\u2019s Adaptive Weighted Attention Network for Haystack Detection in Airborne SAR Imagery","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7134904875","doi":"https://doi.org/10.1109/access.2026.3672644"},"language":"en","primary_location":{"id":"doi:10.1109/access.2026.3672644","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3672644","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.2026.3672644","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Jianmin Hu","orcid":"https://orcid.org/0000-0002-1045-2524"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210137199","display_name":"Aerospace Information Research Institute","ror":"https://ror.org/0419fj215","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210137199"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jianmin Hu","raw_affiliation_strings":["GBA Branch of Aerospace Information Research Institute, Chinese Academy of Sciences, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-1045-2524","affiliations":[{"raw_affiliation_string":"GBA Branch of Aerospace Information Research Institute, Chinese Academy of Sciences, Guangzhou, China","institution_ids":["https://openalex.org/I4210137199","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128742636","display_name":"Cheng Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210137199","display_name":"Aerospace Information Research Institute","ror":"https://ror.org/0419fj215","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210137199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cheng Chen","raw_affiliation_strings":["GBA Branch of Aerospace Information Research Institute, Chinese Academy of Sciences, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"GBA Branch of Aerospace Information Research Institute, Chinese Academy of Sciences, Guangzhou, China","institution_ids":["https://openalex.org/I4210137199","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114193624","display_name":"Jinting Xie","orcid":null},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210137199","display_name":"Aerospace Information Research Institute","ror":"https://ror.org/0419fj215","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210137199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinting Xie","raw_affiliation_strings":["GBA Branch of Aerospace Information Research Institute, Chinese Academy of Sciences, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"GBA Branch of Aerospace Information Research Institute, Chinese Academy of Sciences, Guangzhou, China","institution_ids":["https://openalex.org/I4210137199","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073178391","display_name":"Boyue Li","orcid":null},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210137199","display_name":"Aerospace Information Research Institute","ror":"https://ror.org/0419fj215","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210137199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Boyue Li","raw_affiliation_strings":["GBA Branch of Aerospace Information Research Institute, Chinese Academy of Sciences, Guangzhou, China"],"raw_orcid":"https://orcid.org/0009-0007-1193-2953","affiliations":[{"raw_affiliation_string":"GBA Branch of Aerospace Information Research Institute, Chinese Academy of Sciences, Guangzhou, China","institution_ids":["https://openalex.org/I4210137199","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005555999","display_name":"Aguan Hong","orcid":"https://orcid.org/0009-0001-9154-3427"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Aguan Hong","raw_affiliation_strings":["South China University of Technology, Guangzhou, China"],"raw_orcid":"https://orcid.org/0009-0001-9154-3427","affiliations":[{"raw_affiliation_string":"South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128722784","display_name":"Xiang Yi","orcid":null},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiang Yi","raw_affiliation_strings":["South China University of Technology, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-0330-737X","affiliations":[{"raw_affiliation_string":"South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Huanjun Chen","orcid":"https://orcid.org/0000-0003-4699-009X"},"institutions":[{"id":"https://openalex.org/I4391767867","display_name":"State Key Laboratory of Optoelectronic Materials and Technology","ror":"https://ror.org/010fszt18","country_code":null,"type":"facility","lineage":["https://openalex.org/I157773358","https://openalex.org/I4391767867"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huanjun Chen","raw_affiliation_strings":["State Key Laboratory of Optoelectronic Materials and Technologies, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-4699-009X","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Optoelectronic Materials and Technologies, Guangzhou, China","institution_ids":["https://openalex.org/I4391767867"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128798293","display_name":"Yan Shen","orcid":null},"institutions":[{"id":"https://openalex.org/I4391767867","display_name":"State Key Laboratory of Optoelectronic Materials and Technology","ror":"https://ror.org/010fszt18","country_code":null,"type":"facility","lineage":["https://openalex.org/I157773358","https://openalex.org/I4391767867"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yan Shen","raw_affiliation_strings":["State Key Laboratory of Optoelectronic Materials and Technologies, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-7357-5716","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Optoelectronic Materials and Technologies, Guangzhou, China","institution_ids":["https://openalex.org/I4391767867"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128745733","display_name":"Zhenyu Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenyu Yang","raw_affiliation_strings":["School of Electronics and Information Technology, Sun Yat-sen University, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronics and Information Technology, Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5128710678","display_name":"Xinwen Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinwen Zhang","raw_affiliation_strings":["School of Electronics and Information Technology, Sun Yat-sen University, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronics and Information Technology, Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":10,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210137199"],"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":1,"citation_normalized_percentile":{"value":0.4335602,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"14","issue":null,"first_page":"47085","last_page":"47105"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.3391000032424927,"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"}},"topics":[{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.3391000032424927,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.13289999961853027,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/T10616","display_name":"Smart Agriculture and AI","score":0.10989999771118164,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/synthetic-aperture-radar","display_name":"Synthetic aperture radar","score":0.7170000076293945},{"id":"https://openalex.org/keywords/upsampling","display_name":"Upsampling","score":0.6937000155448914},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5598000288009644},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5550000071525574},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.446399986743927},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.42500001192092896},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.39430001378059387},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.38089999556541443},{"id":"https://openalex.org/keywords/haystack","display_name":"Haystack","score":0.376800000667572}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8379999995231628},{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.7170000076293945},{"id":"https://openalex.org/C110384440","wikidata":"https://www.wikidata.org/wiki/Q1143270","display_name":"Upsampling","level":3,"score":0.6937000155448914},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6031000018119812},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5598000288009644},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5550000071525574},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.446399986743927},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.42500001192092896},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.396699994802475},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.39430001378059387},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.38089999556541443},{"id":"https://openalex.org/C13424479","wikidata":"https://www.wikidata.org/wiki/Q5687237","display_name":"Haystack","level":2,"score":0.376800000667572},{"id":"https://openalex.org/C2993807640","wikidata":"https://www.wikidata.org/wiki/Q103709453","display_name":"Attention network","level":2,"score":0.358599990606308},{"id":"https://openalex.org/C39399123","wikidata":"https://www.wikidata.org/wiki/Q1348989","display_name":"Earth observation","level":3,"score":0.3465999960899353},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.33980000019073486},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2879999876022339},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.28529998660087585},{"id":"https://openalex.org/C10929652","wikidata":"https://www.wikidata.org/wiki/Q7279985","display_name":"Radar imaging","level":3,"score":0.28439998626708984},{"id":"https://openalex.org/C151416825","wikidata":"https://www.wikidata.org/wiki/Q934791","display_name":"Quadtree","level":2,"score":0.2793000042438507},{"id":"https://openalex.org/C203595873","wikidata":"https://www.wikidata.org/wiki/Q25389927","display_name":"Change detection","level":2,"score":0.2775999903678894},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.2761000096797943},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.26489999890327454},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.2628999948501587},{"id":"https://openalex.org/C2781395549","wikidata":"https://www.wikidata.org/wiki/Q4680762","display_name":"Adaptive sampling","level":3,"score":0.25589999556541443},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.25540000200271606},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.25459998846054077}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2026.3672644","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3672644","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:doaj.org/article:96b503cb2a4849efa37b045871847671","is_oa":true,"landing_page_url":"https://doaj.org/article/96b503cb2a4849efa37b045871847671","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 14, Pp 47085-47105 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2026.3672644","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3672644","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":[{"display_name":"Zero hunger","id":"https://metadata.un.org/sdg/2","score":0.6860536932945251}],"awards":[{"id":"https://openalex.org/G5129643677","display_name":null,"funder_award_id":"62334005","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":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"With":[0],"the":[1,61,75,119,122,150,161,169,230,235],"advancement":[2],"of":[3,63,105,113,121,152,220,234],"agricultural":[4],"technology,":[5],"China\u2019s":[6],"annual":[7],"grain":[8,18,35,42],"production":[9],"has":[10],"significantly":[11,159],"increased,":[12],"placing":[13],"growing":[14],"demands":[15],"on":[16,57,144],"efficient":[17],"transportation":[19],"planning.":[20],"In":[21,118],"order":[22],"to":[23,86,138,148],"in":[24,41,65,94,214,224],"assist":[25],"establish":[26],"a":[27,80,193,217],"fast":[28],"and":[29,45,78,90,130,158,178,204,232],"reliable":[30],"statistical":[31],"method":[32],"for":[33,60,110],"estimating":[34],"storage":[36],"distribution,":[37],"thereby":[38],"supporting":[39],"decision-making":[40],"logistics,":[43],"transportation,":[44],"resource":[46],"allocation,":[47],"this":[48],"paper":[49],"proposes":[50],"an":[51,131],"AdaptiveWeighted":[52],"Attention":[53,83,133],"Network":[54],"(AWANet)":[55],"based":[56,143],"deep":[58],"learning":[59],"detection":[62],"haystacks":[64],"Synthetic":[66],"Aperture":[67],"Radar":[68],"(SAR)":[69],"imagery.":[70],"AWANet":[71,187],"is":[72,126,136],"built":[73],"upon":[74],"YOLOv11":[76],"framework":[77],"incorporates":[79],"novel":[81],"Weighted":[82],"Module":[84,134],"(WAM)":[85],"enhance":[87],"feature":[88,146,163],"extraction":[89],"object":[91],"modeling":[92],"capabilities":[93],"Airborne":[95],"SAR":[96],"imagery":[97],"by":[98],"integrating":[99],"three":[100],"attention":[101,107,141],"mechanisms.":[102],"The":[103,206],"introduction":[104],"trainable":[106],"weights":[108,142],"allows":[109],"dynamic":[111],"balancing":[112],"these":[114],"mechanisms":[115],"during":[116,155],"backpropagation.":[117],"neck":[120],"network,":[123],"upsampling":[124],"operation":[125],"replaced":[127],"with":[128,216],"deconvolution,":[129],"Adaptive":[132],"(AAM)":[135],"proposed":[137,207,236],"compute":[139],"adaptive":[140],"intermediate-layer":[145],"maps":[147],"mitigates":[149],"loss":[151,171],"low-level":[153],"information":[154],"deep-layer":[156],"processing":[157],"enhances":[160],"network\u2019s":[162],"representation":[164],"capability.":[165],"Additionally,":[166],"we":[167],"adopt":[168],"Focal-EIoU":[170],"function,":[172],"which":[173],"prioritizes":[174],"difficult":[175],"training":[176],"samples":[177],"leverages":[179],"rich":[180],"geometric":[181],"information.":[182],"Experimental":[183],"evaluation":[184],"demonstrates":[185],"that":[186],"achieves":[188],"57.07%":[189],"mAP@50-95":[190],"while":[191],"maintaining":[192],"lightweight":[194],"architecture,":[195],"outperforming":[196],"common":[197],"models":[198],"such":[199],"as":[200],"SSD,":[201],"RT-DETR,":[202],"YOLOv8,":[203],"YOLOv11.":[205],"model":[208],"consistently":[209],"surpasses":[210],"all":[211],"compared":[212],"methods":[213],"mAP@50-95,":[215],"notable":[218],"improvement":[219],"4.79%":[221],"over":[222],"SSD":[223],"particular.":[225],"These":[226],"results":[227],"fully":[228],"validate":[229],"effectiveness":[231],"superiority":[233],"approach.":[237]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-05-07T13:39:58.223016","created_date":"2026-03-12T00:00:00"}
