{"id":"https://openalex.org/W2977548365","doi":"https://doi.org/10.1109/ijcnn.2019.8851878","title":"DeepIQ: A Human-Inspired AI System for Solving IQ Test Problems","display_name":"DeepIQ: A Human-Inspired AI System for Solving IQ Test Problems","publication_year":2019,"publication_date":"2019-07-01","ids":{"openalex":"https://openalex.org/W2977548365","doi":"https://doi.org/10.1109/ijcnn.2019.8851878","mag":"2977548365"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2019.8851878","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2019.8851878","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":["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/A5073814691","display_name":"Jacek Ma\u0144dziuk","orcid":"https://orcid.org/0000-0003-0947-028X"},"institutions":[{"id":"https://openalex.org/I108403487","display_name":"Warsaw University of Technology","ror":"https://ror.org/00y0xnp53","country_code":"PL","type":"education","lineage":["https://openalex.org/I108403487"]}],"countries":["PL"],"is_corresponding":true,"raw_author_name":"Jacek Mandziuk","raw_affiliation_strings":["Faculty of Mathematics and Information Science, Warsaw University of Technology, Warsaw, Poland"],"affiliations":[{"raw_affiliation_string":"Faculty of Mathematics and Information Science, Warsaw University of Technology, Warsaw, Poland","institution_ids":["https://openalex.org/I108403487"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076496438","display_name":"Adam \u017bychowski","orcid":"https://orcid.org/0000-0003-0026-5183"},"institutions":[{"id":"https://openalex.org/I108403487","display_name":"Warsaw University of Technology","ror":"https://ror.org/00y0xnp53","country_code":"PL","type":"education","lineage":["https://openalex.org/I108403487"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Adam Zychowski","raw_affiliation_strings":["Faculty of Mathematics and Information Science, Warsaw University of Technology, Warsaw, Poland"],"affiliations":[{"raw_affiliation_string":"Faculty of Mathematics and Information Science, Warsaw University of Technology, Warsaw, Poland","institution_ids":["https://openalex.org/I108403487"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5073814691"],"corresponding_institution_ids":["https://openalex.org/I108403487"],"apc_list":null,"apc_paid":null,"fwci":1.5353,"has_fulltext":false,"cited_by_count":35,"citation_normalized_percentile":{"value":0.83796171,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":98,"max":100},"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/T11577","display_name":"Cognitive Abilities and Testing","score":0.9853000044822693,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11577","display_name":"Cognitive Abilities and Testing","score":0.9853000044822693,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9225999712944031,"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/T10885","display_name":"Gene expression and cancer classification","score":0.9118000268936157,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"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"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.688441812992096},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.6808858513832092},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.6626642942428589},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.65289306640625},{"id":"https://openalex.org/keywords/ravens-progressive-matrices","display_name":"Raven's Progressive Matrices","score":0.5707879066467285},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5659372210502625},{"id":"https://openalex.org/keywords/human-intelligence","display_name":"Human intelligence","score":0.5460157990455627},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4940789043903351},{"id":"https://openalex.org/keywords/test-set","display_name":"Test set","score":0.4933845102787018},{"id":"https://openalex.org/keywords/intelligence-quotient","display_name":"Intelligence quotient","score":0.49096372723579407},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.48553749918937683},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4746984839439392},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.47324973344802856},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4712771773338318},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.4421481192111969},{"id":"https://openalex.org/keywords/cosine-similarity","display_name":"Cosine similarity","score":0.4378976821899414},{"id":"https://openalex.org/keywords/cognition","display_name":"Cognition","score":0.09237030148506165}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.688441812992096},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.6808858513832092},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.6626642942428589},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.65289306640625},{"id":"https://openalex.org/C173354102","wikidata":"https://www.wikidata.org/wiki/Q1510887","display_name":"Raven's Progressive Matrices","level":3,"score":0.5707879066467285},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5659372210502625},{"id":"https://openalex.org/C105409693","wikidata":"https://www.wikidata.org/wiki/Q5937824","display_name":"Human intelligence","level":2,"score":0.5460157990455627},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4940789043903351},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.4933845102787018},{"id":"https://openalex.org/C166047926","wikidata":"https://www.wikidata.org/wiki/Q170277","display_name":"Intelligence quotient","level":3,"score":0.49096372723579407},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.48553749918937683},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4746984839439392},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.47324973344802856},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4712771773338318},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.4421481192111969},{"id":"https://openalex.org/C2780762811","wikidata":"https://www.wikidata.org/wiki/Q1784941","display_name":"Cosine similarity","level":3,"score":0.4378976821899414},{"id":"https://openalex.org/C169900460","wikidata":"https://www.wikidata.org/wiki/Q2200417","display_name":"Cognition","level":2,"score":0.09237030148506165},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"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/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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":1,"locations":[{"id":"doi:10.1109/ijcnn.2019.8851878","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2019.8851878","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"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7599999904632568,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W10359634","https://openalex.org/W80679475","https://openalex.org/W97534101","https://openalex.org/W99485931","https://openalex.org/W134043265","https://openalex.org/W1607658174","https://openalex.org/W1988488214","https://openalex.org/W1994565286","https://openalex.org/W2048921251","https://openalex.org/W2055986305","https://openalex.org/W2062152791","https://openalex.org/W2062687369","https://openalex.org/W2064705449","https://openalex.org/W2067737176","https://openalex.org/W2072691187","https://openalex.org/W2102419107","https://openalex.org/W2145482038","https://openalex.org/W2151575489","https://openalex.org/W2157762168","https://openalex.org/W2165698076","https://openalex.org/W2173959313","https://openalex.org/W2394870034","https://openalex.org/W2587580318","https://openalex.org/W2761955404","https://openalex.org/W2798610041","https://openalex.org/W2804180102","https://openalex.org/W2952828155","https://openalex.org/W4307979480","https://openalex.org/W6600459173","https://openalex.org/W6603368007","https://openalex.org/W6682402173","https://openalex.org/W6711938316","https://openalex.org/W6745038159","https://openalex.org/W6752056529","https://openalex.org/W6842957089"],"related_works":["https://openalex.org/W2391016522","https://openalex.org/W2118453636","https://openalex.org/W2025072637","https://openalex.org/W590145548","https://openalex.org/W3025165827","https://openalex.org/W2139837723","https://openalex.org/W4362602006","https://openalex.org/W2357102914","https://openalex.org/W4281641179","https://openalex.org/W2188756514"],"abstract_inverted_index":{"This":[0,131],"paper":[1,152],"presents":[2],"a":[3,32,40,64,97,111,182],"neural":[4],"network":[5],"approach":[6],"to":[7,38,58,76,105,140],"solving":[8,82],"the":[9,78,144,151,186],"most":[10,187],"common":[11],"type":[12,121],"of":[13,29,43,53,60,70,81,86,88,114,122,136,143,165,190],"human":[14,178],"IQ":[15,49,123,166],"test":[16,106],"problems":[17],"-":[18],"Raven's":[19],"Progressive":[20],"Matrices":[21],"(RMs).":[22],"The":[23],"proposed":[24],"DeepIQ":[25,73],"system":[26],"is":[27,36,74,135,148],"composed":[28],"three":[30],"modules:":[31],"deep":[33],"autoencoder":[34],"which":[35],"trained":[37],"learn":[39,77],"feature-based":[41],"representation":[42],"various":[44],"figure":[45],"images":[46],"used":[47],"in":[48,90,96,150,197],"tests,":[50],"an":[51],"ensemble":[52],"shallow":[54],"multilayer":[55],"perceptrons":[56],"applied":[57],"detection":[59],"feature":[61],"differences,":[62],"and":[63,147,170,193],"scoring":[65],"module":[66],"use":[67],"for":[68,128],"assessment":[69],"candidate":[71],"answers.":[72],"able":[75],"underlying":[79],"principles":[80],"RMs":[83,169],"(the":[84],"importance":[85,138],"similarity":[87],"figures":[89],"shape,":[91],"rotation,":[92],"size":[93],"or":[94,119],"shading)":[95],"domain-independent":[98],"way,":[99],"that":[100],"allows":[101],"its":[102],"subsequent":[103],"application":[104],"instances":[107,192],"constructed":[108],"based":[109],"on":[110,153,185],"different":[112,155],"set":[113],"figures,":[115],"never":[116],"seen":[117],"before,":[118],"another":[120],"problem,":[124],"with":[125],"no":[126],"requirement":[127],"additional":[129],"training.":[130],"transfer":[132],"learning":[133],"property":[134],"paramount":[137],"due":[139],"scarce":[141],"availability":[142],"real":[145],"data,":[146],"demonstrated":[149],"two":[154,162],"RM":[156,191],"data":[157],"sets,":[158],"as":[159,161],"well":[160],"distinct":[163],"types":[164],"tasks":[167],"(solving":[168],"odd-one-out":[171,198],"problems).":[172],"Experimental":[173],"results":[174],"are":[175],"promising,":[176],"excelling":[177],"average":[179],"scores":[180],"by":[181],"large":[183],"margin":[184],"challenging":[188],"subset":[189],"exceeding":[194],"90%":[195],"accuracy":[196],"tests.":[199]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":17},{"year":2022,"cited_by_count":8}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}