{"id":"https://openalex.org/W4415736097","doi":"https://doi.org/10.1142/s0218194025500913","title":"Adaptive Fine-Grained Attention and Multi-Scale Fusion Mechanism for Real-Time Small Traffic Object Detection","display_name":"Adaptive Fine-Grained Attention and Multi-Scale Fusion Mechanism for Real-Time Small Traffic Object Detection","publication_year":2025,"publication_date":"2025-10-31","ids":{"openalex":"https://openalex.org/W4415736097","doi":"https://doi.org/10.1142/s0218194025500913"},"language":"en","primary_location":{"id":"doi:10.1142/s0218194025500913","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218194025500913","pdf_url":null,"source":{"id":"https://openalex.org/S131442419","display_name":"International Journal of Software Engineering and Knowledge Engineering","issn_l":"0218-1940","issn":["0218-1940","1793-6403"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Software Engineering and Knowledge Engineering","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/A5029391141","display_name":"Longzhe Han","orcid":"https://orcid.org/0000-0003-2063-0598"},"institutions":[{"id":"https://openalex.org/I4210132981","display_name":"Ningxia Water Conservancy","ror":"https://ror.org/02p2qrw13","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210132981"]},{"id":"https://openalex.org/I4210140142","display_name":"Jiangxi Provincial Institute of Water Resources Planning and Design","ror":"https://ror.org/043my4k18","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210140142"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Longzhe Han","raw_affiliation_strings":["Jiangxi Province Engineering Research Center for Intelligent Processing and Early Warning, Technology of Water Conservancy Big Data, Jiangxi University of Water Resources and Electric Power, Nanchang 330099, China"],"raw_orcid":"https://orcid.org/0000-0003-2063-0598","affiliations":[{"raw_affiliation_string":"Jiangxi Province Engineering Research Center for Intelligent Processing and Early Warning, Technology of Water Conservancy Big Data, Jiangxi University of Water Resources and Electric Power, Nanchang 330099, China","institution_ids":["https://openalex.org/I4210132981","https://openalex.org/I4210140142"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Li Chen","orcid":"https://orcid.org/0009-0000-7498-6480"},"institutions":[{"id":"https://openalex.org/I4210132981","display_name":"Ningxia Water Conservancy","ror":"https://ror.org/02p2qrw13","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210132981"]},{"id":"https://openalex.org/I4210140142","display_name":"Jiangxi Provincial Institute of Water Resources Planning and Design","ror":"https://ror.org/043my4k18","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210140142"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Chen","raw_affiliation_strings":["Jiangxi Province Engineering Research Center for Intelligent Processing and Early Warning, Technology of Water Conservancy Big Data, Jiangxi University of Water Resources and Electric Power, Nanchang 330099, China"],"raw_orcid":"https://orcid.org/0009-0000-7498-6480","affiliations":[{"raw_affiliation_string":"Jiangxi Province Engineering Research Center for Intelligent Processing and Early Warning, Technology of Water Conservancy Big Data, Jiangxi University of Water Resources and Electric Power, Nanchang 330099, China","institution_ids":["https://openalex.org/I4210132981","https://openalex.org/I4210140142"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Hui Zhang","orcid":"https://orcid.org/0009-0005-8370-6299"},"institutions":[{"id":"https://openalex.org/I4210132981","display_name":"Ningxia Water Conservancy","ror":"https://ror.org/02p2qrw13","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210132981"]},{"id":"https://openalex.org/I4210140142","display_name":"Jiangxi Provincial Institute of Water Resources Planning and Design","ror":"https://ror.org/043my4k18","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210140142"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hui Zhang","raw_affiliation_strings":["Jiangxi Province Engineering Research Center for Intelligent Processing and Early Warning, Technology of Water Conservancy Big Data, Jiangxi University of Water Resources and Electric Power, Nanchang 330099, China"],"raw_orcid":"https://orcid.org/0009-0005-8370-6299","affiliations":[{"raw_affiliation_string":"Jiangxi Province Engineering Research Center for Intelligent Processing and Early Warning, Technology of Water Conservancy Big Data, Jiangxi University of Water Resources and Electric Power, Nanchang 330099, China","institution_ids":["https://openalex.org/I4210132981","https://openalex.org/I4210140142"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101701667","display_name":"Jiahao Zhao","orcid":"https://orcid.org/0000-0002-4528-2879"},"institutions":[{"id":"https://openalex.org/I4210132981","display_name":"Ningxia Water Conservancy","ror":"https://ror.org/02p2qrw13","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210132981"]},{"id":"https://openalex.org/I4210140142","display_name":"Jiangxi Provincial Institute of Water Resources Planning and Design","ror":"https://ror.org/043my4k18","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210140142"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jia Zhao","raw_affiliation_strings":["Jiangxi Province Engineering Research Center for Intelligent Processing and Early Warning, Technology of Water Conservancy Big Data, Jiangxi University of Water Resources and Electric Power, Nanchang 330099, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Jiangxi Province Engineering Research Center for Intelligent Processing and Early Warning, Technology of Water Conservancy Big Data, Jiangxi University of Water Resources and Electric Power, Nanchang 330099, China","institution_ids":["https://openalex.org/I4210132981","https://openalex.org/I4210140142"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Lianghong Lin","orcid":"https://orcid.org/0009-0001-9690-1393"},"institutions":[{"id":"https://openalex.org/I4210132981","display_name":"Ningxia Water Conservancy","ror":"https://ror.org/02p2qrw13","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210132981"]},{"id":"https://openalex.org/I4210140142","display_name":"Jiangxi Provincial Institute of Water Resources Planning and Design","ror":"https://ror.org/043my4k18","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210140142"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lianghong Lin","raw_affiliation_strings":["Jiangxi Province Engineering Research Center for Intelligent Processing and Early Warning, Technology of Water Conservancy Big Data, Jiangxi University of Water Resources and Electric Power, Nanchang 330099, China"],"raw_orcid":"https://orcid.org/0009-0001-9690-1393","affiliations":[{"raw_affiliation_string":"Jiangxi Province Engineering Research Center for Intelligent Processing and Early Warning, Technology of Water Conservancy Big Data, Jiangxi University of Water Resources and Electric Power, Nanchang 330099, China","institution_ids":["https://openalex.org/I4210132981","https://openalex.org/I4210140142"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yiying Zhang","orcid":"https://orcid.org/0000-0003-2131-1257"},"institutions":[{"id":"https://openalex.org/I132369690","display_name":"Tianjin University of Science and Technology","ror":"https://ror.org/018rbtf37","country_code":"CN","type":"education","lineage":["https://openalex.org/I132369690"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yiying Zhang","raw_affiliation_strings":["College of Artificial Intelligence, Tianjin University of Science and Technology, Tianjin 300222, China"],"raw_orcid":"https://orcid.org/0000-0003-2131-1257","affiliations":[{"raw_affiliation_string":"College of Artificial Intelligence, Tianjin University of Science and Technology, Tianjin 300222, China","institution_ids":["https://openalex.org/I132369690"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102779406","display_name":"Yan Liu","orcid":"https://orcid.org/0000-0002-8667-879X"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yan Liu","raw_affiliation_strings":["School of Data Science and Engineering, East China Normal University, Shanghai 200062, China"],"raw_orcid":"https://orcid.org/0000-0002-8667-879X","affiliations":[{"raw_affiliation_string":"School of Data Science and Engineering, East China Normal University, Shanghai 200062, China","institution_ids":["https://openalex.org/I66867065"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.28361874,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"36","issue":"05","first_page":"719","last_page":"742"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9745000004768372,"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":0.9745000004768372,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.003100000089034438,"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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.002899999963119626,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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/object-detection","display_name":"Object detection","score":0.7639999985694885},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.5584999918937683},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5001999735832214},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4927000105381012},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4456000030040741},{"id":"https://openalex.org/keywords/intelligent-transportation-system","display_name":"Intelligent transportation system","score":0.39989998936653137},{"id":"https://openalex.org/keywords/video-tracking","display_name":"Video tracking","score":0.37049999833106995},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35830000042915344},{"id":"https://openalex.org/keywords/pyramid","display_name":"Pyramid (geometry)","score":0.35010001063346863}],"concepts":[{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.7639999985694885},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.763700008392334},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6464999914169312},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.570900022983551},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.5584999918937683},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5001999735832214},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4927000105381012},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4456000030040741},{"id":"https://openalex.org/C47796450","wikidata":"https://www.wikidata.org/wiki/Q508378","display_name":"Intelligent transportation system","level":2,"score":0.39989998936653137},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3718999922275543},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.37049999833106995},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35830000042915344},{"id":"https://openalex.org/C142575187","wikidata":"https://www.wikidata.org/wiki/Q3358290","display_name":"Pyramid (geometry)","level":2,"score":0.35010001063346863},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.34119999408721924},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.32829999923706055},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.32820001244544983},{"id":"https://openalex.org/C155542232","wikidata":"https://www.wikidata.org/wiki/Q736111","display_name":"Optical flow","level":3,"score":0.32199999690055847},{"id":"https://openalex.org/C35525427","wikidata":"https://www.wikidata.org/wiki/Q745881","display_name":"Intrusion detection system","level":2,"score":0.32170000672340393},{"id":"https://openalex.org/C2780624872","wikidata":"https://www.wikidata.org/wiki/Q852453","display_name":"Motion detection","level":3,"score":0.30379998683929443},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.3010999858379364},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.29589998722076416},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.2953000068664551},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.28630000352859497},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.28279998898506165},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.2711000144481659},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.26980000734329224},{"id":"https://openalex.org/C88796919","wikidata":"https://www.wikidata.org/wiki/Q1142907","display_name":"Backbone network","level":2,"score":0.2538999915122986},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2524000108242035}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1142/s0218194025500913","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218194025500913","pdf_url":null,"source":{"id":"https://openalex.org/S131442419","display_name":"International Journal of Software Engineering and Knowledge Engineering","issn_l":"0218-1940","issn":["0218-1940","1793-6403"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Software Engineering and Knowledge Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2921568846","display_name":"\u9762\u5411\u4fe1\u606f\u4e2d\u5fc35G\u7f51\u7edc\u7684\u81ea\u9002\u5e94\u8fb9\u7f18\u7f13\u5b58\u7b56\u7565\u53ca\u6570\u636e\u5206\u6d41\u65b9\u6cd5\u7814\u7a76","funder_award_id":"61962036","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":25,"referenced_works":["https://openalex.org/W2565639579","https://openalex.org/W2570343428","https://openalex.org/W2594258618","https://openalex.org/W2752825721","https://openalex.org/W2963037989","https://openalex.org/W2964479623","https://openalex.org/W2973315405","https://openalex.org/W3122799380","https://openalex.org/W3128183952","https://openalex.org/W3138516171","https://openalex.org/W3203003533","https://openalex.org/W4294805043","https://openalex.org/W4295927775","https://openalex.org/W4311532677","https://openalex.org/W4315641800","https://openalex.org/W4319226720","https://openalex.org/W4385839827","https://openalex.org/W4386324994","https://openalex.org/W4393150006","https://openalex.org/W4394797470","https://openalex.org/W4401479755","https://openalex.org/W4402754006","https://openalex.org/W4402775306","https://openalex.org/W4406164208","https://openalex.org/W4406238060"],"related_works":[],"abstract_inverted_index":{"Unmanned":[0],"Aerial":[1],"Vehicle":[2],"(UAV)":[3],"video":[4],"surveillance":[5],"has":[6],"become":[7],"indispensable":[8],"for":[9,158],"intelligent":[10],"transportation":[11],"systems,":[12],"autonomous":[13],"driving":[14],"and":[15,30,42,59,79,134,149,185,193,195,212],"unmanned":[16],"vehicle":[17],"applications.":[18],"However,":[19],"traffic":[20,70,160],"objects":[21],"captured":[22],"from":[23,39],"high":[24],"altitudes":[25],"typically":[26],"exhibit":[27],"small":[28,69,109,159],"sizes":[29],"weak":[31],"feature":[32,111,142,153,166],"representation,":[33],"while":[34,127,207],"being":[35],"susceptible":[36],"to":[37,107,163,202],"interference":[38],"UAV":[40],"motion":[41],"complex":[43],"road":[44],"environments,":[45],"resulting":[46],"in":[47,183,187],"detection":[48,53,72,162],"challenges.":[49],"Additionally,":[50],"multi-scale":[51,80,165],"object":[52,71,110,161],"requires":[54],"a":[55,67,92,151],"balance":[56],"between":[57],"accuracy":[58],"efficiency.":[60],"To":[61],"address":[62],"these":[63],"issues,":[64],"we":[65,90],"propose":[66,150],"real-time":[68],"method":[73],"based":[74],"on":[75,170,189,197],"adaptive":[76,102],"fine-grained":[77,103],"attention":[78,105,147],"fusion":[81],"mechanism.":[82],"Building":[83],"upon":[84],"the":[85,123,139,171,176,190,198,203],"Real-Time":[86,96],"Detection":[87,97],"Transformer":[88,98],"(RT-DETR),":[89],"construct":[91],"Small":[93],"Object":[94],"Enhanced":[95],"(SOE-RTDETR)":[99],"with":[100],"an":[101],"channel":[104],"block":[106],"enhance":[108],"extraction.":[112],"The":[113],"SOE-RTDETR":[114,178],"incorporates":[115],"CSP-Dilated":[116],"Reparam":[117],"Residual":[118],"Blocks":[119],"(CSP-DRRB)":[120],"that":[121,175],"expand":[122],"convolutional":[124],"receptive":[125],"field":[126],"maintaining":[128,208],"computational":[129,213],"efficiency":[130],"through":[131],"depthwise":[132],"convolution":[133],"reparameterization.":[135],"We":[136],"further":[137],"optimize":[138],"attention-based":[140],"intra-scale":[141],"interaction":[143],"module":[144],"using":[145],"deformable":[146],"mechanism":[148],"bidirectional":[152],"pyramid":[154],"network":[155],"specifically":[156],"designed":[157],"strengthen":[164],"fusion.":[167],"Experimental":[168],"results":[169],"VisDrone2019":[172],"dataset":[173],"demonstrate":[174],"proposed":[177],"achieves":[179],"improvements":[180],"of":[181],"2.9%":[182],"mAP@50":[184],"2.3%":[186,194],"mAP@50:95":[188],"validation":[191],"set,":[192],"1.5%":[196],"test":[199],"set":[200],"compared":[201],"baseline":[204],"RT-DETR-r18":[205],"model,":[206],"equivalent":[209],"model":[210],"size":[211],"cost.":[214]},"counts_by_year":[],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-31T00:00:00"}
