{"id":"https://openalex.org/W4200286702","doi":"https://doi.org/10.1007/s40747-021-00588-3","title":"Efficient structural pseudoinverse learning-based hierarchical representation learning for skin lesion classification","display_name":"Efficient structural pseudoinverse learning-based hierarchical representation learning for skin lesion classification","publication_year":2021,"publication_date":"2021-12-23","ids":{"openalex":"https://openalex.org/W4200286702","doi":"https://doi.org/10.1007/s40747-021-00588-3"},"language":"en","primary_location":{"id":"doi:10.1007/s40747-021-00588-3","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s40747-021-00588-3","pdf_url":"https://link.springer.com/content/pdf/10.1007/s40747-021-00588-3.pdf","source":{"id":"https://openalex.org/S3035462843","display_name":"Complex & Intelligent Systems","issn_l":"2198-6053","issn":["2198-6053","2199-4536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Complex & Intelligent Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://link.springer.com/content/pdf/10.1007/s40747-021-00588-3.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5045752328","display_name":"Xiaodan Deng","orcid":"https://orcid.org/0000-0001-5773-1195"},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaodan Deng","raw_affiliation_strings":["School of Systems Science, Beijing Normal University, Beijing, 100875, China"],"affiliations":[{"raw_affiliation_string":"School of Systems Science, Beijing Normal University, Beijing, 100875, China","institution_ids":["https://openalex.org/I25254941"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081412949","display_name":"Qian Yin","orcid":"https://orcid.org/0000-0002-0354-5490"},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Qian Yin","raw_affiliation_strings":["School of Artificial Intelligence, Beijing Normal University, Beijing, 100875, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Beijing Normal University, Beijing, 100875, China","institution_ids":["https://openalex.org/I25254941"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020083340","display_name":"Ping Guo","orcid":"https://orcid.org/0000-0002-7122-1084"},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ping Guo","raw_affiliation_strings":["School of Systems Science, Beijing Normal University, Beijing, 100875, China"],"affiliations":[{"raw_affiliation_string":"School of Systems Science, Beijing Normal University, Beijing, 100875, China","institution_ids":["https://openalex.org/I25254941"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5081412949"],"corresponding_institution_ids":["https://openalex.org/I25254941"],"apc_list":{"value":1320,"currency":"GBP","value_usd":1619},"apc_paid":{"value":1320,"currency":"GBP","value_usd":1619},"fwci":0.7157,"has_fulltext":true,"cited_by_count":11,"citation_normalized_percentile":{"value":0.74158877,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"8","issue":"2","first_page":"1445","last_page":"1457"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10392","display_name":"Cutaneous Melanoma Detection and Management","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2730","display_name":"Oncology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T10392","display_name":"Cutaneous Melanoma Detection and Management","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2730","display_name":"Oncology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9702000021934509,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T12357","display_name":"Digital Media Forensic Detection","score":0.9653000235557556,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7874441146850586},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6903448700904846},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6885582208633423},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6779699325561523},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6408044695854187},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6117283701896667},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.5994590520858765},{"id":"https://openalex.org/keywords/moore\u2013penrose-pseudoinverse","display_name":"Moore\u2013Penrose pseudoinverse","score":0.55013108253479},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.47333675622940063},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4382723569869995},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4159834384918213},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.4152188301086426},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1297612488269806},{"id":"https://openalex.org/keywords/inverse","display_name":"Inverse","score":0.07672995328903198}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7874441146850586},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6903448700904846},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6885582208633423},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6779699325561523},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6408044695854187},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6117283701896667},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.5994590520858765},{"id":"https://openalex.org/C21556879","wikidata":"https://www.wikidata.org/wiki/Q43219517","display_name":"Moore\u2013Penrose pseudoinverse","level":3,"score":0.55013108253479},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.47333675622940063},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4382723569869995},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4159834384918213},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.4152188301086426},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1297612488269806},{"id":"https://openalex.org/C207467116","wikidata":"https://www.wikidata.org/wiki/Q4385666","display_name":"Inverse","level":2,"score":0.07672995328903198},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/s40747-021-00588-3","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s40747-021-00588-3","pdf_url":"https://link.springer.com/content/pdf/10.1007/s40747-021-00588-3.pdf","source":{"id":"https://openalex.org/S3035462843","display_name":"Complex & Intelligent Systems","issn_l":"2198-6053","issn":["2198-6053","2199-4536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Complex & Intelligent Systems","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1007/s40747-021-00588-3","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s40747-021-00588-3","pdf_url":"https://link.springer.com/content/pdf/10.1007/s40747-021-00588-3.pdf","source":{"id":"https://openalex.org/S3035462843","display_name":"Complex & Intelligent Systems","issn_l":"2198-6053","issn":["2198-6053","2199-4536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Complex & Intelligent Systems","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2169308062","display_name":null,"funder_award_id":"2018AAA0100203","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G4077282791","display_name":null,"funder_award_id":"2018AAA0100203","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G466649759","display_name":null,"funder_award_id":"2017Y","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G4777390799","display_name":null,"funder_award_id":"U2031136","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5053610798","display_name":null,"funder_award_id":"2017YFC","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G8199041989","display_name":null,"funder_award_id":"2018AAA010020","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G8340078520","display_name":null,"funder_award_id":"2017YF","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4200286702.pdf","grobid_xml":"https://content.openalex.org/works/W4200286702.grobid-xml"},"referenced_works_count":33,"referenced_works":["https://openalex.org/W241806773","https://openalex.org/W1981276685","https://openalex.org/W2011430131","https://openalex.org/W2029683515","https://openalex.org/W2097117768","https://openalex.org/W2100495367","https://openalex.org/W2125485651","https://openalex.org/W2126324288","https://openalex.org/W2163922914","https://openalex.org/W2169369279","https://openalex.org/W2183341477","https://openalex.org/W2194775991","https://openalex.org/W2564782580","https://openalex.org/W2581082771","https://openalex.org/W2592160412","https://openalex.org/W2604272474","https://openalex.org/W2612806369","https://openalex.org/W2769215776","https://openalex.org/W2794825826","https://openalex.org/W2804383999","https://openalex.org/W2807032201","https://openalex.org/W2895067176","https://openalex.org/W2911818805","https://openalex.org/W2914959431","https://openalex.org/W2922510944","https://openalex.org/W2943964494","https://openalex.org/W2956801253","https://openalex.org/W2963446712","https://openalex.org/W2963946669","https://openalex.org/W2991840431","https://openalex.org/W3087275632","https://openalex.org/W3102785203","https://openalex.org/W4236654676"],"related_works":["https://openalex.org/W2770176672","https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W3167935049","https://openalex.org/W3029198973","https://openalex.org/W3048601286","https://openalex.org/W2965925734","https://openalex.org/W4309346246"],"abstract_inverted_index":{"Abstract":[0],"The":[1,129],"success":[2],"of":[3,111,176,199,207],"deep":[4,100,119,163],"learning":[5,25,90,101,132,164],"in":[6,65,219],"skin":[7,40,75,112,147,177],"lesion":[8,41,113,148,178],"classification":[9,110],"mainly":[10],"depends":[11],"on":[12],"the":[13,18,58,66,109,139,146,168,174,185,193,205,220],"ultra-deep":[14],"neural":[15,121],"network":[16,96,122],"and":[17,30,45,69,99,117,223],"significantly":[19],"large":[20,31],"training":[21,26,160,206],"data":[22,46,59,200],"set.":[23],"Deep":[24],"is":[27,61,135],"usually":[28],"time-consuming,":[29],"datasets":[32],"with":[33],"labels":[34],"are":[35,53,104,123,151],"hard":[36],"to":[37,73,137,153,156,183],"obtain,":[38],"especially":[39],"images.":[42,114],"Although":[43],"pre-training":[44],"augmentation":[47],"can":[48],"alleviate":[49],"these":[50,79],"issues,":[51],"there":[52],"still":[54],"some":[55],"problems:":[56],"(1)":[57],"domain":[60,201],"not":[62,190],"consistent,":[63],"resulting":[64],"slow":[67,194],"convergence;":[68],"(2)":[70],"low":[71],"robustness":[72],"confusing":[74,208],"lesions.":[76],"To":[77],"solve":[78],"problems,":[80],"we":[81,172],"propose":[82],"an":[83],"efficient":[84],"structural":[85,130],"pseudoinverse":[86,131],"learning-based":[87],"hierarchical":[88,169],"representation":[89,170],"method.":[91],"Preliminary":[92],"feature":[93,97,102,127,165],"extraction,":[94],"shallow":[95,140],"extraction":[98,103],"carried":[105],"out":[106],"respectively":[107],"before":[108],"Gabor":[115],"filter":[116],"pre-trained":[118],"convolutional":[120],"used":[124,136],"for":[125,162],"preliminary":[126],"extraction.":[128,166],"(S-PIL)":[133],"algorithm":[134],"extract":[138],"features.":[141],"Then,":[142],"S-PIL":[143],"preliminarily":[144],"identifies":[145],"images":[149,179],"that":[150],"difficult":[152],"be":[154],"classified":[155],"form":[157],"a":[158],"new":[159],"set":[161],"Through":[167],"learning,":[171],"analyze":[173],"features":[175],"layer":[180,182],"by":[181,197],"improve":[184],"final":[186],"classification.":[187],"Our":[188],"method":[189],"only":[191],"avoid":[192],"convergence":[195],"caused":[196],"inconsistency":[198],"but":[202],"also":[203],"enhances":[204],"examples.":[209],"Without":[210],"using":[211],"additional":[212],"data,":[213],"our":[214],"approach":[215],"outperforms":[216],"existing":[217],"methods":[218],"ISIC":[221,224],"2017":[222],"2018":[225],"datasets.":[226]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1}],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2025-10-10T00:00:00"}