{"id":"https://openalex.org/W2928033176","doi":"https://doi.org/10.1109/ijcnn.2019.8852390","title":"FKIMNet: A Finger Dorsal Image Matching Network Comparing Component (Major, Minor and Nail) Matching with Holistic (Finger Dorsal) Matching","display_name":"FKIMNet: A Finger Dorsal Image Matching Network Comparing Component (Major, Minor and Nail) Matching with Holistic (Finger Dorsal) Matching","publication_year":2019,"publication_date":"2019-07-01","ids":{"openalex":"https://openalex.org/W2928033176","doi":"https://doi.org/10.1109/ijcnn.2019.8852390","mag":"2928033176"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2019.8852390","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2019.8852390","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1904.01289","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Daksh Thapar","orcid":null},"institutions":[{"id":"https://openalex.org/I9579091","display_name":"Indian Institute of Technology Mandi","ror":"https://ror.org/05r9r2f34","country_code":"IN","type":"education","lineage":["https://openalex.org/I9579091"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Daksh Thapar","raw_affiliation_strings":["School of Computing and Electrical Engineering, Indian Institute of Technology Mandi, Mandi, India"],"affiliations":[{"raw_affiliation_string":"School of Computing and Electrical Engineering, Indian Institute of Technology Mandi, Mandi, India","institution_ids":["https://openalex.org/I9579091"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Gaurav Jaswal","orcid":null},"institutions":[{"id":"https://openalex.org/I9579091","display_name":"Indian Institute of Technology Mandi","ror":"https://ror.org/05r9r2f34","country_code":"IN","type":"education","lineage":["https://openalex.org/I9579091"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Gaurav Jaswal","raw_affiliation_strings":["School of Computing and Electrical Engineering, Indian Institute of Technology Mandi, Mandi, India"],"affiliations":[{"raw_affiliation_string":"School of Computing and Electrical Engineering, Indian Institute of Technology Mandi, Mandi, India","institution_ids":["https://openalex.org/I9579091"]}]},{"author_position":"last","author":{"id":null,"display_name":"Aditya Nigam","orcid":null},"institutions":[{"id":"https://openalex.org/I9579091","display_name":"Indian Institute of Technology Mandi","ror":"https://ror.org/05r9r2f34","country_code":"IN","type":"education","lineage":["https://openalex.org/I9579091"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Aditya Nigam","raw_affiliation_strings":["School of Computing and Electrical Engineering, Indian Institute of Technology Mandi, Mandi, India"],"affiliations":[{"raw_affiliation_string":"School of Computing and Electrical Engineering, Indian Institute of Technology Mandi, Mandi, India","institution_ids":["https://openalex.org/I9579091"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I9579091"],"apc_list":null,"apc_paid":null,"fwci":2.0107,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.86984379,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"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/T10828","display_name":"Biometric Identification and Security","score":0.9995999932289124,"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":0.9995999932289124,"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/T11448","display_name":"Face recognition and analysis","score":0.996999979019165,"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/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.9383000135421753,"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/knuckle","display_name":"Knuckle","score":0.8330000042915344},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.7429999709129333},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6116999983787537},{"id":"https://openalex.org/keywords/biometrics","display_name":"Biometrics","score":0.5740000009536743},{"id":"https://openalex.org/keywords/minor","display_name":"Minor (academic)","score":0.5526999831199646},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5185999870300293},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5011000037193298},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.48899999260902405}],"concepts":[{"id":"https://openalex.org/C2775868079","wikidata":"https://www.wikidata.org/wiki/Q794715","display_name":"Knuckle","level":2,"score":0.8330000042915344},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.7429999709129333},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7311999797821045},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6230999827384949},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6116999983787537},{"id":"https://openalex.org/C184297639","wikidata":"https://www.wikidata.org/wiki/Q177765","display_name":"Biometrics","level":2,"score":0.5740000009536743},{"id":"https://openalex.org/C2779760435","wikidata":"https://www.wikidata.org/wiki/Q5396169","display_name":"Minor (academic)","level":2,"score":0.5526999831199646},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5185999870300293},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5011000037193298},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.48899999260902405},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4650000035762787},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4327000081539154},{"id":"https://openalex.org/C140530291","wikidata":"https://www.wikidata.org/wiki/Q1225063","display_name":"Dorsum","level":2,"score":0.38609999418258667},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.374099999666214},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.37400001287460327},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3587000072002411},{"id":"https://openalex.org/C2983787585","wikidata":"https://www.wikidata.org/wiki/Q93586","display_name":"Feature matching","level":3,"score":0.3488999903202057},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.3091999888420105},{"id":"https://openalex.org/C61455927","wikidata":"https://www.wikidata.org/wiki/Q1030529","display_name":"Blossom algorithm","level":3,"score":0.29600000381469727},{"id":"https://openalex.org/C146318809","wikidata":"https://www.wikidata.org/wiki/Q3398332","display_name":"Hand geometry","level":3,"score":0.28769999742507935},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.2721000015735626},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.2711000144481659}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/ijcnn.2019.8852390","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2019.8852390","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1904.01289","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1904.01289","pdf_url":"https://arxiv.org/pdf/1904.01289","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1904.01289","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1904.01289","pdf_url":"https://arxiv.org/pdf/1904.01289","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1030408308","https://openalex.org/W1677182931","https://openalex.org/W1778545351","https://openalex.org/W1997157840","https://openalex.org/W2000521269","https://openalex.org/W2033150480","https://openalex.org/W2036188737","https://openalex.org/W2064282629","https://openalex.org/W2065660439","https://openalex.org/W2093433254","https://openalex.org/W2096540110","https://openalex.org/W2096733369","https://openalex.org/W2099131976","https://openalex.org/W2114631941","https://openalex.org/W2133693315","https://openalex.org/W2194775991","https://openalex.org/W2280932954","https://openalex.org/W2417429787","https://openalex.org/W2490465768","https://openalex.org/W2553035813","https://openalex.org/W2755425156","https://openalex.org/W2759610541","https://openalex.org/W2963901018","https://openalex.org/W6756946244"],"related_works":[],"abstract_inverted_index":{"Current":[0],"finger":[1,67,71,74,91,199,215],"knuckle":[2,75,216],"image":[3,76,217],"recognition":[4],"systems,":[5],"often":[6],"require":[7],"users":[8],"to":[9,129,143,196],"place":[10],"fingers'":[11],"major":[12,183],"or":[13],"minor":[14,48,185],"joints":[15],"flatly":[16],"towards":[17],"the":[18,40,46,63,90,119,123,126,134,153,169],"capturing":[19],"sensor.":[20],"To":[21],"extend":[22],"these":[23],"systems":[24],"for":[25,73],"user":[26],"non-intrusive":[27],"application":[28],"scenarios,":[29],"such":[30],"as":[31,174,176,200],"consumer":[32],"electronics,":[33],"forensic,":[34],"defence":[35],"etc,":[36],"we":[37,94,155],"suggest":[38,80],"matching":[39,92],"full":[41,66,198],"dorsal":[42],"fingers,":[43],"rather":[44],"than":[45],"major/":[47],"region":[49],"of":[50,70,107,125,140,152,172,182,203],"interest":[51],"(ROI)":[52],"alone.":[53],"In":[54,166],"particular,":[55],"this":[56],"paper":[57],"makes":[58],"a":[59,85,96,103,147],"comprehensive":[60],"study":[61],"on":[62],"comparisons":[64],"between":[65,122,136],"and":[68,162,187,223],"fusion":[69,181],"ROI's":[72],"recognition.":[77],"These":[78],"experiments":[79],"that":[81],"using":[82,211],"full-finger,":[83],"provides":[84],"more":[86],"elegant":[87],"solution.":[88],"Addressing":[89],"problem,":[93],"propose":[95],"CNN":[97],"(convolutional":[98],"neural":[99],"network)":[100],"which":[101,117],"creates":[102],"128-D":[104],"feature":[105],"embedding":[106],"an":[108],"image.":[109],"It":[110],"is":[111,209],"trained":[112],"via.":[113],"triplet":[114],"loss":[115],"function,":[116],"enforces":[118],"L2":[120],"distance":[121,135],"embeddings":[124,139],"same":[127],"subject":[128],"be":[130,144],"approaching":[131],"zero,":[132],"whereas":[133],"any":[137],"2":[138],"different":[141],"subjects":[142],"at":[145],"least":[146],"margin.":[148],"For":[149],"precise":[150],"training":[151],"network,":[154],"use":[156],"dynamic":[157],"adaptive":[158],"margin,":[159],"data":[160],"augmentation,":[161],"hard":[163],"negative":[164],"mining.":[165],"distinguished":[167],"experiments,":[168],"individual":[170],"performance":[171],"finger,":[173],"well":[175],"weighted":[177],"sum":[178],"score":[179],"level":[180],"knuckle,":[184,186],"nail":[188],"modalities":[189],"have":[190],"been":[191],"computed,":[192],"justifying":[193],"our":[194],"assumption":[195],"consider":[197],"biometrics":[201],"instead":[202],"its":[204],"counterparts.":[205],"The":[206],"proposed":[207],"method":[208],"evaluated":[210],"two":[212],"publicly":[213],"available":[214],"datasets":[218],"i.e.,":[219],"PolyU":[220,224],"FKP":[221],"dataset":[222],"Contactless":[225],"FKI":[226],"Datasets.":[227]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":1}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2019-04-11T00:00:00"}
