{"id":"https://openalex.org/W7163641340","doi":"https://doi.org/10.1109/tifs.2026.3700801","title":"AHFNet: An Adaptive Hybrid Fusion Network for Robust Multimodal Hand Biometrics Under Unreliable Modalities","display_name":"AHFNet: An Adaptive Hybrid Fusion Network for Robust Multimodal Hand Biometrics Under Unreliable Modalities","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7163641340","doi":"https://doi.org/10.1109/tifs.2026.3700801"},"language":null,"primary_location":{"id":"doi:10.1109/tifs.2026.3700801","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tifs.2026.3700801","pdf_url":null,"source":{"id":"https://openalex.org/S61310614","display_name":"IEEE Transactions on Information Forensics and Security","issn_l":"1556-6013","issn":["1556-6013","1556-6021"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Information Forensics and Security","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/A5137956897","display_name":"Rong Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rong Wu","raw_affiliation_strings":["School of Information Science and Technology, Southwest Jiaotong University, Chengdu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, Southwest Jiaotong University, Chengdu, China","institution_ids":["https://openalex.org/I4800084"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103074756","display_name":"Zhongxia Zhang","orcid":"https://orcid.org/0000-0002-5813-5763"},"institutions":[{"id":"https://openalex.org/I2800372957","display_name":"China Electronics Technology Group Corporation","ror":"https://ror.org/0098hst83","country_code":"CN","type":"company","lineage":["https://openalex.org/I2800372957"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhongxia Zhang","raw_affiliation_strings":["China Electronics Technology Cyber Security Company Ltd., Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0002-5813-5763","affiliations":[{"raw_affiliation_string":"China Electronics Technology Cyber Security Company Ltd., Chengdu, China","institution_ids":["https://openalex.org/I2800372957"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137962351","display_name":"Mingxing Zhang","orcid":"https://orcid.org/0000-0002-4112-1744"},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingxing Zhang","raw_affiliation_strings":["School of Mathematics, Southwest Jiaotong University, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0002-4112-1744","affiliations":[{"raw_affiliation_string":"School of Mathematics, Southwest Jiaotong University, Chengdu, China","institution_ids":["https://openalex.org/I4800084"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5004913173","display_name":"Zhengchun Zhou","orcid":"https://orcid.org/0000-0002-0228-7119"},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhengchun Zhou","raw_affiliation_strings":["School of Information Science and Technology, Southwest Jiaotong University, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0002-0228-7119","affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, Southwest Jiaotong University, Chengdu, China","institution_ids":["https://openalex.org/I4800084"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"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":0.7198946,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"21","issue":null,"first_page":"5691","last_page":"5705"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10828","display_name":"Biometric Identification and Security","score":0.7653999924659729,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10828","display_name":"Biometric Identification and Security","score":0.7653999924659729,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T12740","display_name":"Gait Recognition and Analysis","score":0.07410000264644623,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"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/T11800","display_name":"User Authentication and Security Systems","score":0.03830000013113022,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/modalities","display_name":"Modalities","score":0.6154000163078308},{"id":"https://openalex.org/keywords/biometrics","display_name":"Biometrics","score":0.6050000190734863},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.43470001220703125},{"id":"https://openalex.org/keywords/modality","display_name":"Modality (human\u2013computer interaction)","score":0.4108999967575073},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.3919999897480011},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.3910999894142151},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.35120001435279846}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8288999795913696},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.6154000163078308},{"id":"https://openalex.org/C184297639","wikidata":"https://www.wikidata.org/wiki/Q177765","display_name":"Biometrics","level":2,"score":0.6050000190734863},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5443000197410583},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.43470001220703125},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.4108999967575073},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.3919999897480011},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.3910999894142151},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.35120001435279846},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34869998693466187},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.33090001344680786},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.32839998602867126},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2930999994277954},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.28769999742507935},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.28360000252723694},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.2825999855995178},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.27559998631477356},{"id":"https://openalex.org/C2982962833","wikidata":"https://www.wikidata.org/wiki/Q17092450","display_name":"Information fusion","level":2,"score":0.25699999928474426}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tifs.2026.3700801","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tifs.2026.3700801","pdf_url":null,"source":{"id":"https://openalex.org/S61310614","display_name":"IEEE Transactions on Information Forensics and Security","issn_l":"1556-6013","issn":["1556-6013","1556-6021"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Information Forensics and Security","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1648227201","display_name":null,"funder_award_id":"12501737","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Multimodal":[0],"biometric":[1,83,159],"systems":[2],"face":[3],"critical":[4],"deployment":[5],"challenges":[6],"due":[7],"to":[8,56,80,116,200],"frequent":[9],"partial":[10],"modality":[11,15,104],"missing":[12,61],"and":[13,53],"unreliable":[14],"quality":[16],"(e.g.,":[17],"blurred":[18],"fingerprints).":[19],"Existing":[20],"methods,":[21],"relying":[22],"on":[23,145,155],"unidirectional":[24],"feature":[25,75,84,101,130],"interaction":[26],"or":[27,62],"static":[28],"fusion,":[29],"suffer":[30,205],"catastrophic":[31],"performance":[32],"degradation":[33],"under":[34],"such":[35],"conditions.":[36],"This":[37,211],"paper":[38],"proposes":[39],"an":[40],"adaptive":[41],"hybrid":[42],"fusion":[43,92,137],"network":[44],"(AHFNet)":[45],"for":[46,99],"multimodal":[47,152,169],"hand":[48,158],"recognition,":[49],"which":[50,203],"dynamically":[51,139],"selects":[52],"reweights":[54],"modalities":[55,184],"correct":[57],"errors":[58],"induced":[59],"by":[60],"low-quality":[63],"inputs.":[64],"The":[65],"proposed":[66],"framework":[67],"comprises":[68],"three":[69],"core":[70],"modules.":[71],"Initially,":[72],"a":[73,89,123,133],"wavelet":[74],"extraction":[76],"module":[77,93,111,138],"is":[78,94,214],"implemented":[79],"capturing":[81],"high-frequency":[82],"representations":[85],"across":[86,167,217],"modalities.":[87],"Subsequently,":[88],"dual-path":[90],"dynamic":[91,124,135],"designed":[95],"using":[96],"symmetric":[97],"cross-attention":[98],"bidirectional":[100],"reconstruction,":[102],"preserving":[103],"specificity":[105],"via":[106],"residual":[107],"projections.":[108],"Furthermore,":[109],"this":[110],"employs":[112],"the":[113,120,129],"attention":[114],"mechanism":[115],"perform":[117],"reweighting,":[118],"enabling":[119,148],"construction":[121],"of":[122,151,196],"inter-modal":[125],"compensation":[126],"pathway":[127],"at":[128],"level.":[131],"Finally,":[132],"category-aware":[134],"decision":[136],"generates":[140],"category-level":[141],"weight":[142],"coefficients":[143],"based":[144],"input":[146],"samples,":[147],"sample-adaptive":[149],"optimization":[150],"contributions.":[153],"Experiments":[154],"five":[156,219],"public":[157],"databases":[160],"demonstrate":[161],"AHFNet\u2019s":[162],"superiority":[163],"over":[164,197],"existing":[165,201],"methods":[166],"diverse":[168],"scenarios,":[170],"validating":[171],"its":[172],"broad":[173],"applicability.":[174],"Crucially,":[175],"AHFNet":[176],"emphasizes":[177],"modal":[178],"reliability":[179],"differences.":[180],"Even":[181],"when":[182],"certain":[183],"are":[185],"missing,":[186],"it":[187],"exhibits":[188],"less":[189],"than":[190,208],"5%":[191],"accuracy":[192],"degradation\u2014a":[193],"relative":[194],"improvement":[195],"75%":[198],"compared":[199],"approaches,":[202],"typically":[204],"from":[206],"more":[207],"20%":[209],"degradation.":[210],"enhanced":[212],"robustness":[213],"consistently":[215],"observed":[216],"all":[218],"databases.":[220]},"counts_by_year":[],"updated_date":"2026-06-18T08:10:14.011955","created_date":"2026-06-06T00:00:00"}