{"id":"https://openalex.org/W7126105677","doi":"https://doi.org/10.1109/icfsp67350.2025.11353569","title":"Real-World Logistics Object Detection with YoloV12-OBBBiFPNCBAM: A Lightweight and Accurate Approach","display_name":"Real-World Logistics Object Detection with YoloV12-OBBBiFPNCBAM: A Lightweight and Accurate Approach","publication_year":2025,"publication_date":"2025-09-10","ids":{"openalex":"https://openalex.org/W7126105677","doi":"https://doi.org/10.1109/icfsp67350.2025.11353569"},"language":null,"primary_location":{"id":"doi:10.1109/icfsp67350.2025.11353569","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icfsp67350.2025.11353569","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 10th International Conference on Frontiers of Signal Processing (ICFSP)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5124178028","display_name":"Thien-Van Tran","orcid":null},"institutions":[{"id":"https://openalex.org/I171481255","display_name":"Shibaura Institute of Technology","ror":"https://ror.org/020wjcq07","country_code":"JP","type":"education","lineage":["https://openalex.org/I171481255"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Thien-Van Tran","raw_affiliation_strings":["Shibaura Institute of Technology,Functional Control Systems,Tokyo,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shibaura Institute of Technology,Functional Control Systems,Tokyo,Japan","institution_ids":["https://openalex.org/I171481255"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034493423","display_name":"Ngoc-Tam Bui","orcid":"https://orcid.org/0000-0003-0437-6104"},"institutions":[{"id":"https://openalex.org/I171481255","display_name":"Shibaura Institute of Technology","ror":"https://ror.org/020wjcq07","country_code":"JP","type":"education","lineage":["https://openalex.org/I171481255"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Ngoc-Tam Bui","raw_affiliation_strings":["Shibaura Institute of Technology,Innovative Global Program,Tokyo,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shibaura Institute of Technology,Innovative Global Program,Tokyo,Japan","institution_ids":["https://openalex.org/I171481255"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073937678","display_name":"Phan Xuan Tan","orcid":"https://orcid.org/0000-0002-9592-0226"},"institutions":[{"id":"https://openalex.org/I171481255","display_name":"Shibaura Institute of Technology","ror":"https://ror.org/020wjcq07","country_code":"JP","type":"education","lineage":["https://openalex.org/I171481255"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Phan Xuan Tan","raw_affiliation_strings":["Shibaura Institute of Technology,Innovative Global Program,Tokyo,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shibaura Institute of Technology,Innovative Global Program,Tokyo,Japan","institution_ids":["https://openalex.org/I171481255"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5124252528","display_name":"Hiroshi Hasegawa","orcid":null},"institutions":[{"id":"https://openalex.org/I171481255","display_name":"Shibaura Institute of Technology","ror":"https://ror.org/020wjcq07","country_code":"JP","type":"education","lineage":["https://openalex.org/I171481255"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hiroshi Hasegawa","raw_affiliation_strings":["Shibaura Institute of Technology,College of Systems Engineering and Science,Tokyo,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shibaura Institute of Technology,College of Systems Engineering and Science,Tokyo,Japan","institution_ids":["https://openalex.org/I171481255"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I171481255"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.61781382,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"6","last_page":"10"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9603999853134155,"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":0.9603999853134155,"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.00279999990016222,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T14413","display_name":"Advanced Technologies in Various Fields","score":0.002199999988079071,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/software-deployment","display_name":"Software deployment","score":0.6872000098228455},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.6342999935150146},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5740000009536743},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5447999835014343},{"id":"https://openalex.org/keywords/scarcity","display_name":"Scarcity","score":0.3497999906539917},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.30480000376701355}],"concepts":[{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.6872000098228455},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6700999736785889},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.6342999935150146},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5740000009536743},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5447999835014343},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4327999949455261},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.40560001134872437},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3882000148296356},{"id":"https://openalex.org/C109747225","wikidata":"https://www.wikidata.org/wiki/Q815758","display_name":"Scarcity","level":2,"score":0.3497999906539917},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.30480000376701355},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.3012999892234802},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.29589998722076416},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.2955000102519989},{"id":"https://openalex.org/C81293917","wikidata":"https://www.wikidata.org/wiki/Q4189534","display_name":"System deployment","level":3,"score":0.28780001401901245},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.257099986076355}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icfsp67350.2025.11353569","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icfsp67350.2025.11353569","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 10th International Conference on Frontiers of Signal Processing (ICFSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.5188063383102417,"display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":4,"referenced_works":["https://openalex.org/W3164104137","https://openalex.org/W4310173039","https://openalex.org/W4320002812","https://openalex.org/W4395006924"],"related_works":[],"abstract_inverted_index":{"With":[0],"the":[1,62,85,92,110,117],"rapid":[2],"advancement":[3],"of":[4,109],"logistics,":[5],"we":[6,25,60],"propose":[7],"a":[8,31,35,68],"method":[9],"for":[10,47,121],"measuring":[11],"object":[12],"dimensions":[13],"and":[14,39,57,71,112],"detecting":[15],"damaged":[16],"parcels":[17],"to":[18,82,100],"improve":[19],"operational":[20],"quality.":[21],"In":[22],"this":[23,105],"study,":[24],"build":[26],"our":[27],"model":[28,88],"based":[29],"on":[30],"dataset":[32],"collected":[33],"in":[34,96,124],"real-world":[36],"logistics":[37,126],"environment":[38],"address":[40],"data":[41,48],"scarcity":[42],"by":[43,66],"employing":[44],"Stable":[45],"Diffusion":[46],"augmentation.":[49],"To":[50],"enhance":[51],"accuracy":[52,79,97],"while":[53],"maintaining":[54],"computational":[55],"efficiency":[56],"inference":[58],"speed,":[59],"optimize":[61],"standard":[63],"YOLO":[64],"architecture":[65],"integrating":[67],"BiFPN":[69],"neck":[70],"CBAM":[72],"attention":[73],"mechanism.":[74],"Our":[75],"approach":[76],"improves":[77],"detection":[78],"significantly\u2014from":[80],"0.809":[81],"0.927.":[83],"Furthermore,":[84],"proposed":[86],"YOLOv12-BiFPN-CBAM":[87],"not":[89],"only":[90,107],"surpasses":[91],"current":[93],"state-of-the-art":[94],"YOLOv12-nano":[95],"(from":[98],"0.917":[99],"0.927)":[101],"but":[102],"also":[103],"achieves":[104],"with":[106],"65%":[108],"parameters":[111],"FLOPs.":[113],"These":[114],"results":[115],"demonstrate":[116],"model\u2019s":[118],"strong":[119],"potential":[120],"practical":[122],"deployment":[123],"real":[125],"scenarios.":[127]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2026-01-30T00:00:00"}
