{"id":"https://openalex.org/W4416250853","doi":"https://doi.org/10.1109/ijcnn64981.2025.11227959","title":"Multimodal Object Detection by Adaptive Channel Enhancement and Attention Fusion","display_name":"Multimodal Object Detection by Adaptive Channel Enhancement and Attention Fusion","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W4416250853","doi":"https://doi.org/10.1109/ijcnn64981.2025.11227959"},"language":null,"primary_location":{"id":"doi:10.1109/ijcnn64981.2025.11227959","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11227959","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-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/A5066830610","display_name":"Mei Yaqi","orcid":null},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yaqi Mei","raw_affiliation_strings":["Beihang University,School of Software,Beijing,China"],"affiliations":[{"raw_affiliation_string":"Beihang University,School of Software,Beijing,China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023476317","display_name":"Tianyuan Zhang","orcid":"https://orcid.org/0000-0001-9874-6828"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianyuan Zhang","raw_affiliation_strings":["Beihang University,School of Computer Science and Engineering,Beijing,China"],"affiliations":[{"raw_affiliation_string":"Beihang University,School of Computer Science and Engineering,Beijing,China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087082349","display_name":"Huobin Tan","orcid":"https://orcid.org/0000-0003-3113-6552"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huobin Tan","raw_affiliation_strings":["Beihang University,School of Software,Beijing,China"],"affiliations":[{"raw_affiliation_string":"Beihang University,School of Software,Beijing,China","institution_ids":["https://openalex.org/I82880672"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5066830610"],"corresponding_institution_ids":["https://openalex.org/I82880672"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.37369974,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.8708999752998352,"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":0.8708999752998352,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.027300000190734863,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.01860000006854534,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.671500027179718},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.6351000070571899},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.569100022315979},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.5374000072479248},{"id":"https://openalex.org/keywords/modalities","display_name":"Modalities","score":0.4352000057697296},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.429500013589859},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.42260000109672546},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.40299999713897705}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7613999843597412},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.671500027179718},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.64410001039505},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6351000070571899},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.569100022315979},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.5374000072479248},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.4352000057697296},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.429500013589859},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.42260000109672546},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.40299999713897705},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.3903999924659729},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.3698999881744385},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.35830000042915344},{"id":"https://openalex.org/C2982962833","wikidata":"https://www.wikidata.org/wiki/Q17092450","display_name":"Information fusion","level":2,"score":0.3449000120162964},{"id":"https://openalex.org/C173414695","wikidata":"https://www.wikidata.org/wiki/Q5510276","display_name":"Fusion mechanism","level":4,"score":0.3353999853134155},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.3310999870300293},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.3292999863624573},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.320499986410141},{"id":"https://openalex.org/C189693848","wikidata":"https://www.wikidata.org/wiki/Q6031064","display_name":"Information exchange","level":2,"score":0.29739999771118164},{"id":"https://openalex.org/C2781122975","wikidata":"https://www.wikidata.org/wiki/Q16928266","display_name":"Semantic feature","level":2,"score":0.27559998631477356},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.26919999718666077},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.26089999079704285},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2581000030040741},{"id":"https://openalex.org/C2988416141","wikidata":"https://www.wikidata.org/wiki/Q6031139","display_name":"Information loss","level":2,"score":0.25060001015663147}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn64981.2025.11227959","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11227959","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1536680647","https://openalex.org/W2102605133","https://openalex.org/W2161969291","https://openalex.org/W2164598857","https://openalex.org/W2176924101","https://openalex.org/W2193145675","https://openalex.org/W2570343428","https://openalex.org/W2884367402","https://openalex.org/W2929607865","https://openalex.org/W2948153973","https://openalex.org/W2963037989","https://openalex.org/W2965912241","https://openalex.org/W3034552520","https://openalex.org/W3096609285","https://openalex.org/W3118570274","https://openalex.org/W3118934234","https://openalex.org/W3138516171","https://openalex.org/W3151956566","https://openalex.org/W3158128549","https://openalex.org/W3168074788","https://openalex.org/W3207919963","https://openalex.org/W4200631567","https://openalex.org/W4224247218","https://openalex.org/W4285118488","https://openalex.org/W4288375226","https://openalex.org/W4293584584","https://openalex.org/W4319301128","https://openalex.org/W4319969359","https://openalex.org/W4379528676","https://openalex.org/W4382119971","https://openalex.org/W4385801610","https://openalex.org/W4386189887","https://openalex.org/W4402351385"],"related_works":[],"abstract_inverted_index":{"\u2014Cross-modal":[0],"feature":[1,82,93,116,131],"fusion":[2,28,51],"is":[3,122],"a":[4],"critical":[5],"research":[6],"area":[7],"in":[8,46,102,156,161,167,185],"multimodal":[9,92,186],"object":[10,187],"detection,":[11],"focusing":[12],"on":[13,135],"integrating":[14],"features":[15,106],"extracted":[16],"from":[17,107],"different":[18],"modalities":[19],"to":[20,35,124,182],"retain":[21],"richer":[22],"semantic":[23],"information.":[24],"While":[25],"several":[26],"advanced":[27],"strategies":[29],"have":[30],"been":[31],"proposed,":[32],"most":[33],"fail":[34],"effectively":[36],"address":[37,64],"the":[38,57,81,96,112,136,147],"interaction":[39,89,178],"of":[40,60,114,152],"complementary":[41],"information":[42,48,88,177],"between":[43],"modalities,":[44,85,109],"resulting":[45],"suboptimal":[47],"exchange":[49],"and":[50,74,90,138,154,159,163,165,179],"that":[52,142,172],"do":[53],"not":[54],"fully":[55],"leverage":[56],"intrinsic":[58],"characteristics":[59],"each":[61,103],"modality.":[62],"To":[63],"these":[65],"challenges,":[66],"this":[67],"paper":[68],"introduces":[69],"an":[70,119],"Adaptive":[71],"Channel":[72],"Enhancement":[73],"Attention":[75],"Fusion":[76],"(ACAF)":[77],"module,":[78],"which":[79],"bridges":[80],"gaps":[83],"across":[84],"enabling":[86],"smooth":[87],"attention-based":[91],"integration.":[94],"Specifically,":[95],"module":[97],"adaptively":[98],"reweights":[99],"weaker":[100],"channels":[101],"modality":[104],"using":[105],"other":[108],"thereby":[110],"enhancing":[111],"expressiveness":[113],"single-modal":[115],"representations.":[117],"Additionally,":[118],"attention":[120],"mechanism":[121],"employed":[123],"capture":[125],"multidimensional":[126],"cross-modal":[127,176],"relationships,":[128],"facilitating":[129],"efficient":[130],"fusion.":[132],"Experimental":[133],"results":[134],"DroneVehicle":[137],"VEDAI":[139],"datasets":[140],"demonstrate":[141],"our":[143],"method":[144],"significantly":[145],"outperforms":[146],"baseline":[148],"models,":[149],"achieving":[150],"improvements":[151],"3.0%":[153,164],"2.4%":[155],"recall,":[157],"2.1%":[158],"1.7%":[160],"mAP@50,":[162],"4.6%":[166],"mAP@50:95,":[168],"respectively.":[169],"This":[170],"shows":[171],"channel":[173],"reweighting":[174],"enhances":[175],"fusion,":[180],"leading":[181],"superior":[183],"performance":[184],"detection.":[188]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-11-14T00:00:00"}