{"id":"https://openalex.org/W2731168235","doi":"https://doi.org/10.2352/issn.2470-1173.2017.14.hvei-113","title":"Methods and measurements to compare men against machines","display_name":"Methods and measurements to compare men against machines","publication_year":2017,"publication_date":"2017-01-29","ids":{"openalex":"https://openalex.org/W2731168235","doi":"https://doi.org/10.2352/issn.2470-1173.2017.14.hvei-113","mag":"2731168235"},"language":"en","primary_location":{"id":"doi:10.2352/issn.2470-1173.2017.14.hvei-113","is_oa":false,"landing_page_url":"https://doi.org/10.2352/issn.2470-1173.2017.14.hvei-113","pdf_url":null,"source":{"id":"https://openalex.org/S4210227276","display_name":"Electronic Imaging","issn_l":"2470-1173","issn":["2470-1173"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Electronic Imaging","raw_type":"journal-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/A5043258699","display_name":"Felix A. Wichmann","orcid":"https://orcid.org/0000-0002-2592-634X"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Felix A. Wichmann","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102182401","display_name":"David Janssen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"David H. J. Janssen","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043113119","display_name":"Robert Geirhos","orcid":"https://orcid.org/0000-0001-7698-3187"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Robert Geirhos","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102990844","display_name":"Guillermo Aguilar","orcid":"https://orcid.org/0000-0003-0970-5720"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guillermo Aguilar","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025465517","display_name":"Heiko H. Sch\u00fctt","orcid":"https://orcid.org/0000-0002-2491-5710"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Heiko H. Sch\u00fctt","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058680814","display_name":"Marianne Maertens","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Marianne Maertens","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5061457780","display_name":"Matthias Bethge","orcid":"https://orcid.org/0000-0002-6417-7812"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Matthias Bethge","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5043258699"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.9244,"has_fulltext":false,"cited_by_count":23,"citation_normalized_percentile":{"value":0.73411899,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"29","issue":"14","first_page":"36","last_page":"45"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10427","display_name":"Visual perception and processing mechanisms","score":0.8704000115394592,"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":0.8704000115394592,"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/T12389","display_name":"Infrared Target Detection Methodologies","score":0.8026999831199646,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11605","display_name":"Visual Attention and Saliency Detection","score":0.7354999780654907,"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/computer-science","display_name":"Computer science","score":0.762078046798706},{"id":"https://openalex.org/keywords/computational-model","display_name":"Computational model","score":0.7330102920532227},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6739656329154968},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6023704409599304},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5906018614768982},{"id":"https://openalex.org/keywords/vision-science","display_name":"Vision science","score":0.5672552585601807},{"id":"https://openalex.org/keywords/cognitive-neuroscience-of-visual-object-recognition","display_name":"Cognitive neuroscience of visual object recognition","score":0.5567596554756165},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.5206288695335388},{"id":"https://openalex.org/keywords/trustworthiness","display_name":"Trustworthiness","score":0.46927347779273987},{"id":"https://openalex.org/keywords/human-visual-system-model","display_name":"Human visual system model","score":0.4574200212955475},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.4259647727012634},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.42292657494544983},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.42266613245010376},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.3817380368709564},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.17962148785591125},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.07218095660209656}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.762078046798706},{"id":"https://openalex.org/C66024118","wikidata":"https://www.wikidata.org/wiki/Q1122506","display_name":"Computational model","level":2,"score":0.7330102920532227},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6739656329154968},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6023704409599304},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5906018614768982},{"id":"https://openalex.org/C200220432","wikidata":"https://www.wikidata.org/wiki/Q7936208","display_name":"Vision science","level":2,"score":0.5672552585601807},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.5567596554756165},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.5206288695335388},{"id":"https://openalex.org/C153701036","wikidata":"https://www.wikidata.org/wiki/Q659974","display_name":"Trustworthiness","level":2,"score":0.46927347779273987},{"id":"https://openalex.org/C160086991","wikidata":"https://www.wikidata.org/wiki/Q5939193","display_name":"Human visual system model","level":3,"score":0.4574200212955475},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.4259647727012634},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.42292657494544983},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.42266613245010376},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.3817380368709564},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.17962148785591125},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.07218095660209656},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.2352/issn.2470-1173.2017.14.hvei-113","is_oa":false,"landing_page_url":"https://doi.org/10.2352/issn.2470-1173.2017.14.hvei-113","pdf_url":null,"source":{"id":"https://openalex.org/S4210227276","display_name":"Electronic Imaging","issn_l":"2470-1173","issn":["2470-1173"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Electronic Imaging","raw_type":"journal-article"},{"id":"pmh:oai:pure.mpg.de:item_2564844","is_oa":false,"landing_page_url":"http://hdl.handle.net/21.11116/0000-0001-176E-B","pdf_url":null,"source":{"id":"https://openalex.org/S4306400654","display_name":"MPG.PuRe (Max Planck Society)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I149899117","host_organization_name":"Max Planck Society","host_organization_lineage":["https://openalex.org/I149899117"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Human Vision and Electronic Imaging (HVEI 2017)","raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4312417841","https://openalex.org/W4321369474","https://openalex.org/W2915754718","https://openalex.org/W4299822940","https://openalex.org/W2279398222","https://openalex.org/W2970686063","https://openalex.org/W3000866861","https://openalex.org/W2955560448","https://openalex.org/W2801801420","https://openalex.org/W2808506981"],"abstract_inverted_index":{"Recent":[0],"advances":[1,22,78],"in":[2,5,23,31,79,82,92],"computational":[3,68,80,102],"models":[4,34,59,69,81,103,111,154,180],"vision":[6,33,84,88],"science":[7,85],"have":[8,29,104,135,176],"considerably":[9],"furthered":[10],"our":[11],"understanding":[12],"of":[13,35,70],"human":[14,44,74,119,140,170,182],"visual":[15,75],"perception.":[16],"At":[17],"the":[18,40,71,100],"same":[19],"time,":[20,42],"rapid":[21],"convolutional":[24],"deep":[25],"neural":[26],"networks":[27],"(DNNs)":[28],"resulted":[30],"computer":[32,61,87],"object":[36,45],"recognition":[37],"which,":[38],"for":[39,60],"first":[41],"rival":[43],"recognition.":[46],"Furthermore,":[47],"it":[48],"has":[49],"been":[50],"suggested":[51],"that":[52,179],"DNNs":[53],"may":[54,64,112,184],"not":[55],"only":[56,159,172],"be":[57,66,122,185],"successful":[58],"vision,":[62],"but":[63],"also":[65],"good":[67],"monkey":[72],"and":[73,86,95,109,144,181,189],"systems.":[76],"The":[77],"both":[83,197],"pose":[89],"two":[90,93],"challenges":[91],"different":[94,128],"independent":[96],"domains:":[97],"First,":[98],"because":[99],"latest":[101],"much":[105],"higher":[106],"predictive":[107],"accuracy,":[108],"competing":[110],"make":[113],"similar":[114,156,168,187],"predictions,":[115],"we":[116,131,147,175,195],"require":[117],"more":[118],"data":[120,142],"to":[121,124,134,137,151,169],"able":[123],"statistically":[125],"distinguish":[126],"between":[127],"models.":[129],"Thus":[130],"would":[132],"like":[133],"methods":[136],"acquire":[138],"trustworthy":[139],"behavioural":[141],"fast":[143],"easy.":[145],"Second,":[146],"need":[148],"challenging":[149],"experiments":[150],"ascertain":[152],"whether":[153,164],"show":[155],"input-output":[157],"behaviour":[158],"near":[160],"\"ceiling\"":[161],"performance,":[162],"or":[163],"their":[165],"performance":[166],"degrades":[167],"performance:":[171],"then":[173],"do":[174],"strong":[177],"evidence":[178],"observers":[183],"using":[186],"features":[188],"processing":[190],"strategies.":[191],"In":[192],"this":[193],"paper":[194],"address":[196],"challenges.":[198]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":4},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":1}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
