{"id":"https://openalex.org/W3088369722","doi":"https://doi.org/10.1109/access.2020.3025195","title":"Towards an Efficient Segmentation Algorithm for Near-Infrared Eyes Images","display_name":"Towards an Efficient Segmentation Algorithm for Near-Infrared Eyes Images","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3088369722","doi":"https://doi.org/10.1109/access.2020.3025195","mag":"3088369722"},"language":"en","primary_location":{"id":"doi:10.1109/access.2020.3025195","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3025195","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09200989.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09200989.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5076727734","display_name":"Andr\u00e9s Valenzuela","orcid":"https://orcid.org/0000-0002-8172-1541"},"institutions":[{"id":"https://openalex.org/I4210121802","display_name":"Production Development Corporation","ror":"https://ror.org/02qhvm916","country_code":"CL","type":"government","lineage":["https://openalex.org/I4210121802"]}],"countries":["CL"],"is_corresponding":false,"raw_author_name":"Andres Valenzuela","raw_affiliation_strings":["R+D CORFO Center SR-226, TOC Biometric, Santiago, Chile"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"R+D CORFO Center SR-226, TOC Biometric, Santiago, Chile","institution_ids":["https://openalex.org/I4210121802"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028361572","display_name":"Claudia Arellano","orcid":"https://orcid.org/0000-0002-3565-0308"},"institutions":[{"id":"https://openalex.org/I21067949","display_name":"Adolfo Ib\u00e1\u00f1ez University","ror":"https://ror.org/0326knt82","country_code":"CL","type":"education","lineage":["https://openalex.org/I21067949"]}],"countries":["CL"],"is_corresponding":false,"raw_author_name":"Claudia Arellano","raw_affiliation_strings":["Escuela de Negocios, Universidad Adolfo Iba\u00f1ez, Santiago, Chile","R+D Visiometrica, Santiago, Chile"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Escuela de Negocios, Universidad Adolfo Iba\u00f1ez, Santiago, Chile","institution_ids":["https://openalex.org/I21067949"]},{"raw_affiliation_string":"R+D Visiometrica, Santiago, Chile","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5017736954","display_name":"Juan Tapia","orcid":"https://orcid.org/0000-0001-9159-4075"},"institutions":[{"id":"https://openalex.org/I10457146","display_name":"Universidad de Santiago de Chile","ror":"https://ror.org/02ma57s91","country_code":"CL","type":"education","lineage":["https://openalex.org/I10457146"]},{"id":"https://openalex.org/I4210121802","display_name":"Production Development Corporation","ror":"https://ror.org/02qhvm916","country_code":"CL","type":"government","lineage":["https://openalex.org/I4210121802"]}],"countries":["CL"],"is_corresponding":false,"raw_author_name":"Juan E. Tapia","raw_affiliation_strings":["Departamento de Ingenieria Informatica, Universidad de Santiago, Santiago, Chile","R+D CORFO Center SR-226, TOC Biometric, Santiago, Chile"],"raw_orcid":"https://orcid.org/0000-0001-9159-4075","affiliations":[{"raw_affiliation_string":"Departamento de Ingenieria Informatica, Universidad de Santiago, Santiago, Chile","institution_ids":["https://openalex.org/I10457146"]},{"raw_affiliation_string":"R+D CORFO Center SR-226, TOC Biometric, Santiago, Chile","institution_ids":["https://openalex.org/I4210121802"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.0768,"has_fulltext":true,"cited_by_count":21,"citation_normalized_percentile":{"value":0.80079431,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"8","issue":null,"first_page":"171598","last_page":"171607"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9986000061035156,"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9986000061035156,"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/T11707","display_name":"Gaze Tracking and Assistive Technology","score":0.9976000189781189,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/T11438","display_name":"Retinal Imaging and Analysis","score":0.9944000244140625,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8131790161132812},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7148580551147461},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.5627890229225159},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5435064435005188},{"id":"https://openalex.org/keywords/salience","display_name":"Salience (neuroscience)","score":0.4547097980976105},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4397198557853699},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.43288755416870117},{"id":"https://openalex.org/keywords/mobile-device","display_name":"Mobile device","score":0.4204671382904053},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38927921652793884},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.38743454217910767}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8131790161132812},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7148580551147461},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5627890229225159},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5435064435005188},{"id":"https://openalex.org/C108154423","wikidata":"https://www.wikidata.org/wiki/Q1469792","display_name":"Salience (neuroscience)","level":2,"score":0.4547097980976105},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4397198557853699},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.43288755416870117},{"id":"https://openalex.org/C186967261","wikidata":"https://www.wikidata.org/wiki/Q5082128","display_name":"Mobile device","level":2,"score":0.4204671382904053},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38927921652793884},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.38743454217910767},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2020.3025195","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3025195","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09200989.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:5a45e36151cb4967b9429dcf112e4d4a","is_oa":true,"landing_page_url":"https://doaj.org/article/5a45e36151cb4967b9429dcf112e4d4a","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":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 8, Pp 171598-171607 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2020.3025195","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3025195","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09200989.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.47999998927116394,"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9"}],"awards":[{"id":"https://openalex.org/G2599273621","display_name":null,"funder_award_id":"11170189","funder_id":"https://openalex.org/F4320338073","funder_display_name":"Fondo Nacional de Desarrollo Cient\u00edfico y Tecnol\u00f3gico"}],"funders":[{"id":"https://openalex.org/F4320338073","display_name":"Fondo Nacional de Desarrollo Cient\u00edfico y Tecnol\u00f3gico","ror":"https://ror.org/02ap3w078"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3088369722.pdf","grobid_xml":"https://content.openalex.org/works/W3088369722.grobid-xml"},"referenced_works_count":38,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1898703532","https://openalex.org/W1901129140","https://openalex.org/W1910657905","https://openalex.org/W2108598243","https://openalex.org/W2163605009","https://openalex.org/W2194775991","https://openalex.org/W2395611524","https://openalex.org/W2412782625","https://openalex.org/W2559597482","https://openalex.org/W2630837129","https://openalex.org/W2740520864","https://openalex.org/W2769586268","https://openalex.org/W2793444752","https://openalex.org/W2894802018","https://openalex.org/W2919115771","https://openalex.org/W2921445558","https://openalex.org/W2962766617","https://openalex.org/W2963150697","https://openalex.org/W2963446712","https://openalex.org/W2963881378","https://openalex.org/W2964309882","https://openalex.org/W2966593772","https://openalex.org/W2978796584","https://openalex.org/W2996129374","https://openalex.org/W3010820467","https://openalex.org/W3011248942","https://openalex.org/W3011269888","https://openalex.org/W3011456725","https://openalex.org/W3017202003","https://openalex.org/W3100555247","https://openalex.org/W6620707391","https://openalex.org/W6639780620","https://openalex.org/W6639824700","https://openalex.org/W6684191040","https://openalex.org/W6725739302","https://openalex.org/W6739696289","https://openalex.org/W6748481559"],"related_works":["https://openalex.org/W2117158897","https://openalex.org/W4390516098","https://openalex.org/W2795335233","https://openalex.org/W2323464168","https://openalex.org/W2181948922","https://openalex.org/W3034529322","https://openalex.org/W2384362569","https://openalex.org/W2142795561","https://openalex.org/W2515146515","https://openalex.org/W1522196789"],"abstract_inverted_index":{"Semantic":[0],"segmentation":[1,212],"has":[2],"been":[3],"widely":[4],"used":[5,17,160],"for":[6,30,161],"several":[7],"applications,":[8],"including":[9],"the":[10,43,46,65,68,71,88,96,106,118,122,130,199,234,238,245],"detection":[11],"of":[12,42,45,57,67,70,90,98,105,132,225],"eye":[13],"structures.":[14],"This":[15,59,83,227],"is":[16,85,142,177,229],"in":[18,156,198,208,237],"tasks":[19],"such":[20],"as":[21,244],"eye-tracking":[22],"and":[23,35,92,129,147,174,195,218],"gaze":[24],"estimation,":[25],"which":[26],"are":[27],"useful":[28],"techniques":[29,48],"human-computer":[31],"interfaces,":[32],"salience":[33],"detection,":[34],"Virtual":[36],"reality":[37],"(VR),":[38],"amongst":[39,124],"others.":[40],"Most":[41],"state":[44,69],"art":[47,72],"achieve":[49,144],"high":[50],"accuracy":[51],"but":[52],"with":[53,150,170,191,214,221],"a":[54,145,166,168,222],"considerable":[55],"number":[56,97,131],"parameters.":[58],"article":[60],"explores":[61],"alternatives":[62],"to":[63,79,117,135,143,158,249],"improve":[64],"efficiency":[66],"method,":[73],"namely":[74],"DenseNet":[75,169],"Tiramisu,":[76],"when":[77,189],"applied":[78],"NIR":[80],"image":[81],"segmentation.":[82],"task":[84],"not":[86],"trivial;":[87],"reduction":[89],"block":[91],"layers":[93,133,176],"also":[94],"affects":[95],"feature":[99,107],"maps.":[100],"The":[101,139,209,240],"growth":[102],"rate":[103,126],"(k)":[104],"maps":[108],"regulates":[109],"how":[110],"much":[111],"new":[112],"information":[113],"each":[114],"layer":[115],"contributes":[116],"global":[119],"state,":[120],"therefore":[121],"trade-off":[123],"grown":[125],"(k),":[127],"IOU,":[128],"needs":[134],"be":[136,159,250],"carefully":[137],"studied.":[138],"main":[140],"goal":[141],"light-weight":[146],"efficient":[148],"network":[149,184],"fewer":[151],"parameters":[152,220],"than":[153,233],"traditional":[154],"architectures":[155],"order":[157],"mobile":[162],"device":[163],"applications.":[164],"As":[165],"result,":[167],"only":[171,230],"three":[172],"blocks":[173],"ten":[175],"proposed":[178],"(DenseNet10).":[179],"Experiments":[180],"show":[181],"that":[182],"this":[183,203],"achieved":[185],"higher":[186],"IOU":[187,217],"rates":[188],"comparing":[190],"Encoder-Decoder,":[192],"DensetNet56-67-103,":[193],"MaskRCNN,":[194],"DeeplabV3+":[196],"models":[197],"Facebook":[200,210],"database.":[201],"Furthermore,":[202],"method":[204],"reached":[205],"8th":[206],"place":[207,236],"semantic":[211],"challenge":[213],"0.94293":[215],"mean":[216],"202.084":[219],"final":[223],"score":[224,228],"0.97147.":[226],"0,001":[231],"lower":[232],"first":[235],"competition.":[239],"sclera":[241],"was":[242],"identified":[243],"more":[246],"challenging":[247],"structure":[248],"segmented.":[251]},"counts_by_year":[{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":6}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}