iBet uBet web content aggregator. Adding the entire web to your favor.
iBet uBet web content aggregator. Adding the entire web to your favor.



Link to original content: https://api.openalex.org/works/doi:10.3390/S22062133
{"id":"https://openalex.org/W4220752007","doi":"https://doi.org/10.3390/s22062133","title":"Self-Supervised Learning Framework toward State-of-the-Art Iris Image Segmentation","display_name":"Self-Supervised Learning Framework toward State-of-the-Art Iris Image Segmentation","publication_year":2022,"publication_date":"2022-03-09","ids":{"openalex":"https://openalex.org/W4220752007","doi":"https://doi.org/10.3390/s22062133","pmid":"https://pubmed.ncbi.nlm.nih.gov/35336305"},"language":"en","primary_location":{"is_oa":true,"landing_page_url":"https://doi.org/10.3390/s22062133","pdf_url":"https://www.mdpi.com/1424-8220/22/6/2133/pdf?version=1648120030","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true},"type":"article","type_crossref":"journal-article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/22/6/2133/pdf?version=1648120030","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5037469847","display_name":"Wenny Ramadha Putri","orcid":"https://orcid.org/0000-0002-5456-160X"},"institutions":[{"id":"https://openalex.org/I22265921","display_name":"National Central University","ror":"https://ror.org/00944ve71","country_code":"TW","type":"education","lineage":["https://openalex.org/I22265921"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Wenny Ramadha Putri","raw_affiliation_strings":["Department of Computer Science and Information Engineering, National Center University, Taoyuan 32001, Taiwan"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Information Engineering, National Center University, Taoyuan 32001, Taiwan","institution_ids":["https://openalex.org/I22265921"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000828948","display_name":"Shen-Hsuan Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I22265921","display_name":"National Central University","ror":"https://ror.org/00944ve71","country_code":"TW","type":"education","lineage":["https://openalex.org/I22265921"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Shen-Hsuan Liu","raw_affiliation_strings":["Department of Computer Science and Information Engineering, National Center University, Taoyuan 32001, Taiwan"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Information Engineering, National Center University, Taoyuan 32001, Taiwan","institution_ids":["https://openalex.org/I22265921"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004744684","display_name":"Muhammad Saqlain Aslam","orcid":"https://orcid.org/0000-0001-8039-2603"},"institutions":[{"id":"https://openalex.org/I22265921","display_name":"National Central University","ror":"https://ror.org/00944ve71","country_code":"TW","type":"education","lineage":["https://openalex.org/I22265921"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Muhammad Saqlain Aslam","raw_affiliation_strings":["Department of Computer Science and Information Engineering, National Center University, Taoyuan 32001, Taiwan"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Information Engineering, National Center University, Taoyuan 32001, Taiwan","institution_ids":["https://openalex.org/I22265921"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048205934","display_name":"Yung\u2010Hui Li","orcid":"https://orcid.org/0000-0002-0475-3689"},"institutions":[{"id":"https://openalex.org/I4210113837","display_name":"Taiwan Forestry Research Institute","ror":"https://ror.org/01d34a364","country_code":"TW","type":"facility","lineage":["https://openalex.org/I26359584","https://openalex.org/I4210113837"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Yung-Hui Li","raw_affiliation_strings":["AI Research Center, Hon Hai Research Institute, Taipei 114699, Taiwan"],"affiliations":[{"raw_affiliation_string":"AI Research Center, Hon Hai Research Institute, Taipei 114699, Taiwan","institution_ids":["https://openalex.org/I4210113837"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038550838","display_name":"Chin\u2010Chen Chang","orcid":"https://orcid.org/0000-0002-7319-5780"},"institutions":[{"id":"https://openalex.org/I4880106","display_name":"Feng Chia University","ror":"https://ror.org/05vhczg54","country_code":"TW","type":"education","lineage":["https://openalex.org/I4880106"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Chin-Chen Chang","raw_affiliation_strings":["Department of Information Engineering and Computer Science, Feng Chia University, Taichung 40724, Taiwan"],"affiliations":[{"raw_affiliation_string":"Department of Information Engineering and Computer Science, Feng Chia University, Taichung 40724, Taiwan","institution_ids":["https://openalex.org/I4880106"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029325015","display_name":"Jia\u2010Ching Wang","orcid":"https://orcid.org/0000-0003-0024-6732"},"institutions":[{"id":"https://openalex.org/I22265921","display_name":"National Central University","ror":"https://ror.org/00944ve71","country_code":"TW","type":"education","lineage":["https://openalex.org/I22265921"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Jia-Ching Wang","raw_affiliation_strings":["Department of Computer Science and Information Engineering, National Center University, Taoyuan 32001, Taiwan"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Information Engineering, National Center University, Taoyuan 32001, Taiwan","institution_ids":["https://openalex.org/I22265921"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5038550838"],"corresponding_institution_ids":["https://openalex.org/I4880106"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2598,"provenance":"doaj"},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2598,"provenance":"doaj"},"fwci":0.911,"has_fulltext":true,"fulltext_origin":"pdf","cited_by_count":4,"citation_normalized_percentile":{"value":0.677185,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":81,"max":84},"biblio":{"volume":"22","issue":"6","first_page":"2133","last_page":"2133"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10828","display_name":"Biometric Recognition and Security Systems","score":0.9999,"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 Recognition and Security Systems","score":0.9999,"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/T10751","display_name":"Genomic Analysis of Ancient DNA","score":0.9437,"subfield":{"id":"https://openalex.org/subfields/1311","display_name":"Genetics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11448","display_name":"Face Recognition and Analysis Techniques","score":0.9258,"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/iris","display_name":"IRIS (biosensor)","score":0.7312188},{"id":"https://openalex.org/keywords/iris-recognition","display_name":"Iris Recognition","score":0.614811},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature Learning","score":0.576272},{"id":"https://openalex.org/keywords/facial-landmark-detection","display_name":"Facial Landmark Detection","score":0.527991},{"id":"https://openalex.org/keywords/metric-learning","display_name":"Metric Learning","score":0.524708},{"id":"https://openalex.org/keywords/face-spoof-detection","display_name":"Face Spoof Detection","score":0.506596}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.8075134},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7806643},{"id":"https://openalex.org/C2779503344","wikidata":"https://www.wikidata.org/wiki/Q5973514","display_name":"IRIS (biosensor)","level":3,"score":0.7312188},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7116235},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5418355},{"id":"https://openalex.org/C112356035","wikidata":"https://www.wikidata.org/wiki/Q1672722","display_name":"Iris recognition","level":3,"score":0.5280441},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4871547},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.46634597},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.45514256},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.42713955},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36876214},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.32333943},{"id":"https://openalex.org/C184297639","wikidata":"https://www.wikidata.org/wiki/Q177765","display_name":"Biometrics","level":2,"score":0.14226583}],"mesh":[{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":"","qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D007498","descriptor_name":"Iris","qualifier_ui":"","qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D007498","descriptor_name":"Iris","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":false},{"descriptor_ui":"D000069553","descriptor_name":"Supervised Machine Learning","qualifier_ui":"","qualifier_name":null,"is_major_topic":false}],"locations_count":4,"locations":[{"is_oa":true,"landing_page_url":"https://doi.org/10.3390/s22062133","pdf_url":"https://www.mdpi.com/1424-8220/22/6/2133/pdf?version=1648120030","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true},{"is_oa":false,"landing_page_url":"https://doaj.org/article/7f0217f4aa144a288de57c14a61b6f89","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},{"is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8951447","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":["National Institutes of Health"],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true},{"is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35336305","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":["National Institutes of Health"],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":{"is_oa":true,"landing_page_url":"https://doi.org/10.3390/s22062133","pdf_url":"https://www.mdpi.com/1424-8220/22/6/2133/pdf?version=1648120030","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true},"sustainable_development_goals":[],"grants":[],"datasets":[],"versions":[],"referenced_works_count":41,"referenced_works":["https://openalex.org/W1516512487","https://openalex.org/W157158741","https://openalex.org/W1923697677","https://openalex.org/W1979331595","https://openalex.org/W2023296739","https://openalex.org/W2049078578","https://openalex.org/W2102796633","https://openalex.org/W2117015400","https://openalex.org/W2125389028","https://openalex.org/W2133793828","https://openalex.org/W2171759622","https://openalex.org/W2317989223","https://openalex.org/W2412782625","https://openalex.org/W2587540369","https://openalex.org/W2772878363","https://openalex.org/W2774581827","https://openalex.org/W2782757030","https://openalex.org/W2802806477","https://openalex.org/W2803380720","https://openalex.org/W2894802018","https://openalex.org/W2899508538","https://openalex.org/W2904606808","https://openalex.org/W2907088611","https://openalex.org/W2908357147","https://openalex.org/W2909906879","https://openalex.org/W2912685185","https://openalex.org/W2955740297","https://openalex.org/W2963684088","https://openalex.org/W2963748958","https://openalex.org/W2971657673","https://openalex.org/W2996290406","https://openalex.org/W3011990345","https://openalex.org/W3096831136","https://openalex.org/W3129897498","https://openalex.org/W3131902737","https://openalex.org/W3134652006","https://openalex.org/W3196980885","https://openalex.org/W4250059488","https://openalex.org/W4293568373","https://openalex.org/W4301206121","https://openalex.org/W639708223"],"related_works":["https://openalex.org/W4231710054","https://openalex.org/W3213945064","https://openalex.org/W3133795085","https://openalex.org/W2952386695","https://openalex.org/W2759939383","https://openalex.org/W2557390811","https://openalex.org/W2355560018","https://openalex.org/W2162640687","https://openalex.org/W2151970936","https://openalex.org/W2147209541"],"abstract_inverted_index":{"Iris":[0],"segmentation":[1,88,153],"plays":[2],"a":[3,36,62,114,156],"pivotal":[4],"role":[5],"in":[6,16,138],"the":[7,48,52,54,66,78,86,132,160],"iris":[8,24,75,80,87,101],"recognition":[9,25],"system.":[10],"The":[11,46,143],"deep":[12,32],"learning":[13,33],"technique":[14],"developed":[15],"recent":[17],"years":[18],"has":[19],"gradually":[20],"been":[21],"applied":[22],"to":[23,84,90,99,150],"techniques.":[26],"As":[27],"we":[28,60],"all":[29,139],"know,":[30],"applying":[31],"techniques":[34],"requires":[35],"large":[37],"number":[38],"of":[39,50,121,159],"data":[40,124],"sets":[41],"with":[42,155],"high-quality":[43],"manual":[44],"labels.":[45],"larger":[47],"amount":[49,120],"data,":[51],"better":[53],"algorithm":[55,98],"performs.":[56],"In":[57],"this":[58],"paper,":[59],"propose":[61,96],"self-supervised":[63],"framework":[64,115,134,145],"utilizing":[65],"pix2pix":[67],"conditional":[68],"adversarial":[69],"network":[70,89],"for":[71,125],"generating":[72],"unlimited":[73,119],"diversified":[74],"images.":[76],"Then,":[77],"generated":[79,111],"images":[81],"are":[82],"used":[83,141],"train":[85],"achieve":[91],"state-of-the-art":[92],"performance.":[93],"We":[94],"also":[95],"an":[97,118],"generate":[100,117],"masks":[102],"based":[103],"on":[104],"11":[105],"tunable":[106],"parameters,":[107],"which":[108],"can":[109,116,146],"be":[110,147],"randomly.":[112],"Such":[113],"photo-realistic":[122],"training":[123],"down-stream":[126],"tasks.":[127],"Experimental":[128],"results":[129,137],"demonstrate":[130],"that":[131],"proposed":[133,144],"achieved":[135],"promising":[136],"commonly":[140],"metrics.":[142],"easily":[148],"generalized":[149],"any":[151],"object":[152],"task":[154],"simple":[157],"fine-tuning":[158],"mask":[161],"generation":[162],"algorithm.":[163]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4220752007","counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2022,"cited_by_count":2}],"updated_date":"2024-11-20T20:57:27.733918","created_date":"2022-04-03"}