{"id":"https://openalex.org/W4200021562","doi":"https://doi.org/10.1145/3500931.3500950","title":"Shape Features Improve the Encoding Performance of High-level Visual Cortex","display_name":"Shape Features Improve the Encoding Performance of High-level Visual Cortex","publication_year":2021,"publication_date":"2021-10-29","ids":{"openalex":"https://openalex.org/W4200021562","doi":"https://doi.org/10.1145/3500931.3500950"},"language":"en","primary_location":{"id":"doi:10.1145/3500931.3500950","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3500931.3500950","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2nd International Symposium on Artificial Intelligence for Medicine Sciences","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/A5000897139","display_name":"Penghui Ding","orcid":null},"institutions":[{"id":"https://openalex.org/I169689159","display_name":"PLA Information Engineering University","ror":"https://ror.org/00mm1qk40","country_code":"CN","type":"education","lineage":["https://openalex.org/I169689159"]},{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Penghui Ding","raw_affiliation_strings":["Zhengzhou University, PLA Strategy Support, Force Information Engineering University2 Zhengzhou Henan China"],"affiliations":[{"raw_affiliation_string":"Zhengzhou University, PLA Strategy Support, Force Information Engineering University2 Zhengzhou Henan China","institution_ids":["https://openalex.org/I169689159","https://openalex.org/I38877650"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100610540","display_name":"Chi Zhang","orcid":"https://orcid.org/0000-0002-4899-2745"},"institutions":[{"id":"https://openalex.org/I169689159","display_name":"PLA Information Engineering University","ror":"https://ror.org/00mm1qk40","country_code":"CN","type":"education","lineage":["https://openalex.org/I169689159"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chi Zhang","raw_affiliation_strings":["PLA Strategy Support Force, Information Engineering University2, Zhengzhou Henan China"],"affiliations":[{"raw_affiliation_string":"PLA Strategy Support Force, Information Engineering University2, Zhengzhou Henan China","institution_ids":["https://openalex.org/I169689159"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091588180","display_name":"Linyuan Wang","orcid":"https://orcid.org/0000-0003-1087-5911"},"institutions":[{"id":"https://openalex.org/I169689159","display_name":"PLA Information Engineering University","ror":"https://ror.org/00mm1qk40","country_code":"CN","type":"education","lineage":["https://openalex.org/I169689159"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Linyuan Wang","raw_affiliation_strings":["PLA Strategy Support Force, Information Engineering University2, Zhengzhou Henan China"],"affiliations":[{"raw_affiliation_string":"PLA Strategy Support Force, Information Engineering University2, Zhengzhou Henan China","institution_ids":["https://openalex.org/I169689159"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100416940","display_name":"Jingwei Li","orcid":"https://orcid.org/0000-0002-6395-8801"},"institutions":[{"id":"https://openalex.org/I169689159","display_name":"PLA Information Engineering University","ror":"https://ror.org/00mm1qk40","country_code":"CN","type":"education","lineage":["https://openalex.org/I169689159"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingwei Li","raw_affiliation_strings":["PLA Strategy Support Force, Information Engineering University2, Zhengzhou Henan China"],"affiliations":[{"raw_affiliation_string":"PLA Strategy Support Force, Information Engineering University2, Zhengzhou Henan China","institution_ids":["https://openalex.org/I169689159"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100359023","display_name":"Li Tong","orcid":"https://orcid.org/0000-0002-4197-7999"},"institutions":[{"id":"https://openalex.org/I169689159","display_name":"PLA Information Engineering University","ror":"https://ror.org/00mm1qk40","country_code":"CN","type":"education","lineage":["https://openalex.org/I169689159"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Tong","raw_affiliation_strings":["PLA Strategy Support Force, Information Engineering University2, Zhengzhou Henan China"],"affiliations":[{"raw_affiliation_string":"PLA Strategy Support Force, Information Engineering University2, Zhengzhou Henan China","institution_ids":["https://openalex.org/I169689159"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5000897139"],"corresponding_institution_ids":["https://openalex.org/I169689159","https://openalex.org/I38877650"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.15932833,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"101","last_page":"108"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10427","display_name":"Visual perception and processing mechanisms","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10427","display_name":"Visual perception and processing mechanisms","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9973000288009644,"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/T10581","display_name":"Neural dynamics and brain function","score":0.9937000274658203,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7135035395622253},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7114410996437073},{"id":"https://openalex.org/keywords/visual-cortex","display_name":"Visual cortex","score":0.6780519485473633},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6364437937736511},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.6355268955230713},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6292082667350769},{"id":"https://openalex.org/keywords/functional-magnetic-resonance-imaging","display_name":"Functional magnetic resonance imaging","score":0.6160796880722046},{"id":"https://openalex.org/keywords/encode","display_name":"ENCODE","score":0.4867279827594757},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.44648057222366333},{"id":"https://openalex.org/keywords/neuroscience","display_name":"Neuroscience","score":0.14025166630744934},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.09937968850135803}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7135035395622253},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7114410996437073},{"id":"https://openalex.org/C2779345533","wikidata":"https://www.wikidata.org/wiki/Q75785","display_name":"Visual cortex","level":2,"score":0.6780519485473633},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6364437937736511},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.6355268955230713},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6292082667350769},{"id":"https://openalex.org/C2779226451","wikidata":"https://www.wikidata.org/wiki/Q903809","display_name":"Functional magnetic resonance imaging","level":2,"score":0.6160796880722046},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.4867279827594757},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.44648057222366333},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.14025166630744934},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.09937968850135803},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"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/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3500931.3500950","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3500931.3500950","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2nd International Symposium on Artificial Intelligence for Medicine Sciences","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6800000071525574,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1715013381","https://openalex.org/W1903029394","https://openalex.org/W1982374456","https://openalex.org/W1987986413","https://openalex.org/W1995605620","https://openalex.org/W2007226897","https://openalex.org/W2063951486","https://openalex.org/W2071714163","https://openalex.org/W2084686727","https://openalex.org/W2089159943","https://openalex.org/W2108598243","https://openalex.org/W2114789518","https://openalex.org/W2116360511","https://openalex.org/W2117731089","https://openalex.org/W2401447009","https://openalex.org/W2603777577","https://openalex.org/W2605516844","https://openalex.org/W2618530766","https://openalex.org/W2651756715","https://openalex.org/W2755036008","https://openalex.org/W2836088610","https://openalex.org/W2891023557","https://openalex.org/W2963581784","https://openalex.org/W3046394086","https://openalex.org/W3101413939","https://openalex.org/W3124792448","https://openalex.org/W4293209991","https://openalex.org/W4308909683","https://openalex.org/W6605284881","https://openalex.org/W6628927728","https://openalex.org/W6687483927"],"related_works":["https://openalex.org/W2372020181","https://openalex.org/W2156531654","https://openalex.org/W1581723585","https://openalex.org/W4378714697","https://openalex.org/W2294330161","https://openalex.org/W2940472653","https://openalex.org/W2253069048","https://openalex.org/W2804553224","https://openalex.org/W140709781","https://openalex.org/W3214340375"],"abstract_inverted_index":{"The":[0,123],"visual":[1,26,67,73,120,128,133],"encoding":[2,121,134,146],"model":[3,135],"based":[4],"on":[5,35],"the":[6,12,18,36,54,66,71,116,119,132,145],"convolutional":[7],"neural":[8,23],"network":[9,24],"(CNN)":[10],"realizes":[11],"prediction":[13],"of":[14,118,126],"brain":[15],"activity":[16],"from":[17,109],"hierarchical":[19],"similarity":[20],"between":[21],"deep":[22],"and":[25,85,96],"cortex.":[27],"However,":[28],"studies":[29],"have":[30,38],"shown":[31],"that":[32,92,131,139],"CNNs":[33,60,91],"trained":[34],"ImageNet":[37],"a":[39,106],"strong":[40],"texture":[41,94],"bias,":[42],"inconsistent":[43],"with":[44],"human's":[45],"preference":[46],"for":[47,70],"shape":[48,97,141],"discrimination":[49],"in":[50],"image":[51,55,87],"recognition.":[52],"Also,":[53],"features":[56,88,95,110,142],"extracted":[57],"by":[58,137],"pre-trained":[59],"are":[61],"not":[62],"enough":[63],"to":[64,104,111,114],"encode":[65],"cortex,":[68],"especially":[69],"high-level":[72],"cortex":[74],"(HVC).":[75],"Here,":[76],"we":[77,100],"use":[78,101],"functional":[79],"magnetic":[80],"resonance":[81],"imaging":[82],"(fMRI)":[83],"data":[84],"extract":[86],"through":[89],"different":[90,127],"learn":[93],"features.":[98],"Then":[99],"ridge":[102],"regression":[103],"build":[105],"linear":[107],"mapping":[108],"voxel":[112],"response":[113],"achieve":[115],"construction":[117],"models.":[122],"comparative":[124],"analysis":[125],"areas":[129],"indicates":[130],"constructed":[136],"CNN":[138],"learns":[140],"can":[143],"improve":[144],"performance.":[147]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}