{"id":"https://openalex.org/W4411383768","doi":"https://doi.org/10.1177/1088467x251348766","title":"ABSOD: Attention based small object detector for outfalls inspection in aerial images","display_name":"ABSOD: Attention based small object detector for outfalls inspection in aerial images","publication_year":2025,"publication_date":"2025-06-17","ids":{"openalex":"https://openalex.org/W4411383768","doi":"https://doi.org/10.1177/1088467x251348766"},"language":"en","primary_location":{"id":"doi:10.1177/1088467x251348766","is_oa":false,"landing_page_url":"https://doi.org/10.1177/1088467x251348766","pdf_url":null,"source":{"id":"https://openalex.org/S2498839158","display_name":"Intelligent Data Analysis","issn_l":"1088-467X","issn":["1088-467X","1571-4128"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Intelligent Data Analysis: An International Journal","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/A5058552039","display_name":"Zhenjia Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhenjia Li","raw_affiliation_strings":["Department of Electrical Engineering, Dean's Office of Inner Mongolia Technical College of Mechanics and Electrics, Hohhot 010070, Inner Mongolia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Dean's Office of Inner Mongolia Technical College of Mechanics and Electrics, Hohhot 010070, Inner Mongolia","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061866632","display_name":"Shengjun Liang","orcid":"https://orcid.org/0000-0001-8545-7015"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]},{"id":"https://openalex.org/I78675632","display_name":"Beijing Information Science & Technology University","ror":"https://ror.org/04xnqep60","country_code":"CN","type":"education","lineage":["https://openalex.org/I78675632"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shengjun Liang","raw_affiliation_strings":["Key Laboratory of the Ministry of Education for Optoelectronic Measurement Technology and Instrument, Beijing Information Science and Technology University, Beijing 100015, China","School of Mechanical Science &amp; Engineering, Huazhong University of Science and Technology, Wuhan 430074, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of the Ministry of Education for Optoelectronic Measurement Technology and Instrument, Beijing Information Science and Technology University, Beijing 100015, China","institution_ids":["https://openalex.org/I78675632"]},{"raw_affiliation_string":"School of Mechanical Science &amp; Engineering, Huazhong University of Science and Technology, Wuhan 430074, China","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5026352201","display_name":"Mingxin Yu","orcid":"https://orcid.org/0000-0001-8823-0852"},"institutions":[{"id":"https://openalex.org/I78675632","display_name":"Beijing Information Science & Technology University","ror":"https://ror.org/04xnqep60","country_code":"CN","type":"education","lineage":["https://openalex.org/I78675632"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingxin Yu","raw_affiliation_strings":["Key Laboratory of the Ministry of Education for Optoelectronic Measurement Technology and Instrument, Beijing Information Science and Technology University, Beijing 100015, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of the Ministry of Education for Optoelectronic Measurement Technology and Instrument, Beijing Information Science and Technology University, Beijing 100015, China","institution_ids":["https://openalex.org/I78675632"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5061866632"],"corresponding_institution_ids":["https://openalex.org/I47720641","https://openalex.org/I78675632"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.10913769,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"29","issue":"4","first_page":"1062","last_page":"1080"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9997000098228455,"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":0.9997000098228455,"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/T12549","display_name":"Image and Object Detection Techniques","score":0.9991999864578247,"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/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.9965999722480774,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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/aerial-imagery","display_name":"Aerial imagery","score":0.7368908524513245},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.5918455719947815},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.4778568148612976},{"id":"https://openalex.org/keywords/outfall","display_name":"Outfall","score":0.4774949252605438},{"id":"https://openalex.org/keywords/aerial-photography","display_name":"Aerial photography","score":0.4760974645614624},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4560108780860901},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4485538899898529},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4291872978210449},{"id":"https://openalex.org/keywords/aerial-image","display_name":"Aerial image","score":0.4178014397621155},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.40406808257102966},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.33919739723205566},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.12768343091011047},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.06342461705207825}],"concepts":[{"id":"https://openalex.org/C2987819851","wikidata":"https://www.wikidata.org/wiki/Q191839","display_name":"Aerial imagery","level":2,"score":0.7368908524513245},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.5918455719947815},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.4778568148612976},{"id":"https://openalex.org/C110049166","wikidata":"https://www.wikidata.org/wiki/Q2533913","display_name":"Outfall","level":2,"score":0.4774949252605438},{"id":"https://openalex.org/C133214962","wikidata":"https://www.wikidata.org/wiki/Q191839","display_name":"Aerial photography","level":2,"score":0.4760974645614624},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4560108780860901},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4485538899898529},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4291872978210449},{"id":"https://openalex.org/C2776429412","wikidata":"https://www.wikidata.org/wiki/Q4688011","display_name":"Aerial image","level":3,"score":0.4178014397621155},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.40406808257102966},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.33919739723205566},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.12768343091011047},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.06342461705207825},{"id":"https://openalex.org/C87717796","wikidata":"https://www.wikidata.org/wiki/Q146326","display_name":"Environmental engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1177/1088467x251348766","is_oa":false,"landing_page_url":"https://doi.org/10.1177/1088467x251348766","pdf_url":null,"source":{"id":"https://openalex.org/S2498839158","display_name":"Intelligent Data Analysis","issn_l":"1088-467X","issn":["1088-467X","1571-4128"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Intelligent Data Analysis: An International Journal","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":52,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1483870316","https://openalex.org/W2109255472","https://openalex.org/W2549139847","https://openalex.org/W2556967412","https://openalex.org/W2587248218","https://openalex.org/W2949846184","https://openalex.org/W2963037989","https://openalex.org/W2963091558","https://openalex.org/W2991015021","https://openalex.org/W2994619704","https://openalex.org/W3009818596","https://openalex.org/W3013162535","https://openalex.org/W3016641475","https://openalex.org/W3039062423","https://openalex.org/W3042011474","https://openalex.org/W3047731328","https://openalex.org/W3091821294","https://openalex.org/W3114606989","https://openalex.org/W3121020412","https://openalex.org/W3123352549","https://openalex.org/W3134025014","https://openalex.org/W3136117624","https://openalex.org/W3143603362","https://openalex.org/W3156982815","https://openalex.org/W3159678417","https://openalex.org/W3166031957","https://openalex.org/W3169233473","https://openalex.org/W3183734964","https://openalex.org/W3192438490","https://openalex.org/W3194607948","https://openalex.org/W3195537687","https://openalex.org/W3203608457","https://openalex.org/W3204014438","https://openalex.org/W3210586215","https://openalex.org/W4206294875","https://openalex.org/W4207034821","https://openalex.org/W4213200979","https://openalex.org/W4226410580","https://openalex.org/W4283029931","https://openalex.org/W4283746543","https://openalex.org/W4309845474","https://openalex.org/W4312823573","https://openalex.org/W4377229921","https://openalex.org/W4379805280","https://openalex.org/W4384519088","https://openalex.org/W4390190233","https://openalex.org/W4392932888","https://openalex.org/W6743731764","https://openalex.org/W6746034047","https://openalex.org/W6784704298","https://openalex.org/W6847043847"],"related_works":["https://openalex.org/W2372478594","https://openalex.org/W2652346890","https://openalex.org/W2386046054","https://openalex.org/W3205848368","https://openalex.org/W2975420069","https://openalex.org/W4283696875","https://openalex.org/W2976105433","https://openalex.org/W3110585990","https://openalex.org/W4251840164","https://openalex.org/W4385767632"],"abstract_inverted_index":{"Strengthening":[0],"the":[1,15,116,143,152,174,178,195,211,214,230,245,269],"inspection":[2],"of":[3,53,129,142,198,213,226],"outfalls":[4,38,57,92,238,283],"into":[5],"rivers":[6],"and":[7,68,73,118,134,187,192,204,289],"oceans":[8],"can":[9,273],"help":[10],"monitor":[11],"pollutant":[12],"emissions":[13],"to":[14,90,110,146,159,165,250,260,278],"natural":[16],"environment.":[17],"Unmanned":[18],"aerial":[19,95],"vehicle":[20],"(UAV)":[21],"with":[22,221,258,284],"high":[23],"spatial":[24,102,149,161],"resolution":[25],"imagery":[26],"has":[27,233],"become":[28],"a":[29,79,234,275],"more":[30,122,252],"efficient":[31],"method":[32],"for":[33,61,237],"outfall":[34,117,256],"surveys.":[35],"At":[36],"present,":[37],"retrieval":[39],"from":[40],"UAV":[41,285],"images":[42,60],"relies":[43],"on":[44,55,151,242,254],"visual":[45],"interpretation":[46],"by":[47],"skilled":[48],"experts.":[49],"However,":[50],"long":[51],"periods":[52],"concentration":[54],"detecting":[56,185,282],"in":[58,71,94,184,194,281],"high-resolution":[59],"an":[62,100],"expert":[63],"easily":[64],"increase":[65],"mental":[66],"load":[67],"stress,":[69],"resulting":[70],"missing":[72],"false":[74],"detection.":[75,239],"Therefore,":[76],"we":[77,217],"develop":[78],"deep":[80,270],"learning":[81,271],"model,":[82,99],"called":[83],"Attention":[84],"Based":[85],"Small":[86],"Object":[87],"Detector":[88],"(ABSOD),":[89],"perform":[91,160],"detection":[93,182],"images.":[96],"In":[97],"this":[98],"adaptive":[101],"correlation":[103,162],"pyramid":[104],"attention":[105,223,253,262],"(ASCPA)":[106],"network":[107,125,176,232,247],"is":[108,126,145,157,248],"proposed":[109,175],"establish":[111],"long-distance":[112],"region-to-region":[113],"relationships":[114],"between":[115],"its":[119],"surrounding":[120],"information":[121,150],"effectively.":[123],"This":[124],"mainly":[127],"composed":[128],"SPE":[130,144],"(Spatial":[131,136],"Pyramid":[132],"Extractor)":[133],"SCFM":[135,156],"Correlation":[137],"Fusion":[138],"Module).":[139],"The":[140,155,287],"purpose":[141],"extract":[147],"multi-scale":[148],"feature":[153,163],"map.":[154],"used":[158],"recalibration":[164],"selectively":[166],"emphasized":[167],"informative":[168],"features.":[169],"Experimental":[170],"results":[171,220,266],"show":[172,210,228],"that":[173,229,268],"outperforms":[177],"state-of-the-art":[179],"small":[180],"object":[181],"model":[183,288],"outfalls,":[186],"reaches":[188],"45.9%,":[189],"92.8%,":[190],"86.5%":[191],"34.4%":[193],"four":[196],"metrics":[197],"Precision,":[199],"Recall,":[200],"AP":[201,205],"0.5":[202],",":[203,207],"0.5:0.95":[206],"respectively.":[208],"To":[209],"superiority":[212],"ASCPA":[215,231,246],"network,":[216],"compared":[218],"our":[219],"other":[222,261],"mechanisms,":[224],"all":[225],"them":[227],"competitive":[235],"performance":[236],"Moreover,":[240],"based":[241],"visualization":[243],"analysis,":[244],"able":[249],"pay":[251],"true":[255],"objects":[257],"respect":[259],"mechanisms.":[263],"These":[264],"promising":[265],"demonstrate":[267],"algorithm":[272],"be":[274],"feasible":[276],"solution":[277],"assist":[279],"experts":[280],"imagery.":[286],"code":[290],"are":[291],"available":[292],"at":[293],"https://github.com/ISCLab-Bistu/ASCPA-Attention":[294],".":[295]},"counts_by_year":[],"updated_date":"2026-05-03T06:03:33.228499","created_date":"2025-10-10T00:00:00"}
