{"id":"https://openalex.org/W3203961778","doi":"https://doi.org/10.1145/3447527.3474873","title":"A Mobile Tool that Helps Nonexperts Make Sense of Pretrained CNN by Interacting with Their Daily Surroundings","display_name":"A Mobile Tool that Helps Nonexperts Make Sense of Pretrained CNN by Interacting with Their Daily Surroundings","publication_year":2021,"publication_date":"2021-09-23","ids":{"openalex":"https://openalex.org/W3203961778","doi":"https://doi.org/10.1145/3447527.3474873","mag":"3203961778"},"language":"en","primary_location":{"id":"doi:10.1145/3447527.3474873","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3447527.3474873","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Adjunct Publication of the 23rd International Conference on Mobile Human-Computer Interaction","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/A5045321143","display_name":"Chao Wang","orcid":"https://orcid.org/0000-0003-1913-2524"},"institutions":[{"id":"https://openalex.org/I4210112253","display_name":"Honda (Germany)","ror":"https://ror.org/022c1xk47","country_code":"DE","type":"company","lineage":["https://openalex.org/I1283473643","https://openalex.org/I4210112253"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Chao Wang","raw_affiliation_strings":["Honda Research Institute Europe, Germany"],"affiliations":[{"raw_affiliation_string":"Honda Research Institute Europe, Germany","institution_ids":["https://openalex.org/I4210112253"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5014119112","display_name":"Pengcheng An","orcid":"https://orcid.org/0000-0002-7705-2031"},"institutions":[{"id":"https://openalex.org/I151746483","display_name":"University of Waterloo","ror":"https://ror.org/01aff2v68","country_code":"CA","type":"education","lineage":["https://openalex.org/I151746483"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Pengcheng An","raw_affiliation_strings":["David R. Cheriton School of Computer Science University of Waterloo, Canada"],"affiliations":[{"raw_affiliation_string":"David R. Cheriton School of Computer Science University of Waterloo, Canada","institution_ids":["https://openalex.org/I151746483"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5045321143"],"corresponding_institution_ids":["https://openalex.org/I4210112253"],"apc_list":null,"apc_paid":null,"fwci":0.5439,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.73053142,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9988999962806702,"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"}},"topics":[{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9988999962806702,"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9941999912261963,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9929999709129333,"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":0.7480791807174683},{"id":"https://openalex.org/keywords/sense","display_name":"Sense (electronics)","score":0.4622241258621216},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.4519082307815552},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4506247341632843},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.13683679699897766},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.061599940061569214}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7480791807174683},{"id":"https://openalex.org/C143141573","wikidata":"https://www.wikidata.org/wiki/Q7450971","display_name":"Sense (electronics)","level":2,"score":0.4622241258621216},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.4519082307815552},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4506247341632843},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.13683679699897766},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.061599940061569214}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3447527.3474873","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3447527.3474873","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Adjunct Publication of the 23rd International Conference on Mobile Human-Computer Interaction","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.4300000071525574,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W2141200610","https://openalex.org/W2295107390","https://openalex.org/W2616247523","https://openalex.org/W2807910285","https://openalex.org/W2962772482","https://openalex.org/W2963911037","https://openalex.org/W2981731882","https://openalex.org/W3102564565","https://openalex.org/W3160872964"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4385542742","https://openalex.org/W4396701345","https://openalex.org/W2037111888","https://openalex.org/W3170014661"],"abstract_inverted_index":{"Current":[0],"research":[1],"on":[2,23],"explainable":[3,177],"AI":[4,15,25,35,178],"(XAI)":[5],"is":[6,19],"primarily":[7],"aimed":[8],"at":[9],"expert":[10,181],"users":[11,62],"(data":[12],"scientists":[13],"or":[14],"developers).":[16],"However,":[17],"there":[18],"an":[20,57,134],"increasing":[21],"emphasis":[22],"making":[24],"more":[26],"understandable":[27],"to":[28,33,48,63,73,85,96,111,163],"non-experts":[29,50,148],"who":[30],"are":[31],"expected":[32],"use":[34,70,77],"techniques":[36],"but":[37],"have":[38],"limited":[39],"knowledge":[40],"about":[41],"AI.":[42],"We":[43,76,131],"propose":[44],"a":[45,97,116,152],"mobile":[46],"application":[47],"help":[49,112,147],"understand":[51],"convolutional":[52],"neural":[53],"networks":[54],"(CNN)":[55],"in":[56,106,127],"interactive":[58],"way;":[59],"it":[60,145,157],"allows":[61],"taking":[64],"pictures":[65],"of":[66,119,124,170],"surrounding":[67],"objects":[68],"and":[69,109,122,165],"pre-trained":[71,125,153],"CNN":[72,126,154],"recognize":[74],"it.":[75],"the":[78,87,120,128,167],"latest":[79],"XAI":[80],"(Class":[81],"Activation":[82],"Map)":[83],"technology":[84],"visualize":[86],"model":[88],"decision":[89],"(the":[90],"most":[91],"important":[92],"image":[93],"area":[94],"leading":[95],"specific":[98],"result).":[99],"This":[100],"playful":[101],"learning":[102],"tool":[103,136],"was":[104],"implemented":[105],"college":[107],"courses":[108],"found":[110],"design":[113,179],"students":[114],"gain":[115],"vivid":[117],"understanding":[118],"functions":[121],"limitations":[123],"real":[129],"world.":[130],"thereby":[132],"contribute":[133,174],"online":[135],"that":[137],"could":[138,146,173],"be":[139,159],"used":[140,160],"for":[141],"twofold":[142],"purposes:":[143],"first,":[144],"interactively":[149],"learn":[150],"how":[151],"works.":[155],"Second,":[156],"can":[158],"by":[161],"researchers":[162],"probe":[164],"characterize":[166],"non-experts\u2019":[168],"process":[169],"sensemaking,":[171],"which":[172],"insights":[175],"into":[176],"beyond":[180],"users.":[182]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2023,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}