{"id":"https://openalex.org/W4396680818","doi":"https://doi.org/10.1109/access.2024.3397061","title":"Toward Visual Syntactical Understanding","display_name":"Toward Visual Syntactical Understanding","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4396680818","doi":"https://doi.org/10.1109/access.2024.3397061"},"language":"en","primary_location":{"id":"doi:10.1109/access.2024.3397061","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1109/access.2024.3397061","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10520274.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10520274.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5081219427","display_name":"Sayeed Shafayet Chowdhury","orcid":"https://orcid.org/0009-0008-7463-8396"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Sayeed Shafayet Chowdhury","raw_affiliation_strings":["Elmore Family School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, USA"],"affiliations":[{"raw_affiliation_string":"Elmore Family School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, USA","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108892773","display_name":"Soumyadeep Chandra","orcid":"https://orcid.org/0009-0002-0182-3618"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Soumyadeep Chandra","raw_affiliation_strings":["Elmore Family School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, USA"],"affiliations":[{"raw_affiliation_string":"Elmore Family School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, USA","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5031161187","display_name":"Kaushik Roy","orcid":"https://orcid.org/0009-0002-3375-2877"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kaushik Roy","raw_affiliation_strings":["Elmore Family School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, USA"],"affiliations":[{"raw_affiliation_string":"Elmore Family School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, USA","institution_ids":["https://openalex.org/I219193219"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5081219427"],"corresponding_institution_ids":["https://openalex.org/I219193219"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.05266122,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"12","issue":null,"first_page":"64360","last_page":"64375"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9994000196456909,"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"}},"topics":[{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9994000196456909,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9958000183105469,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9886999726295471,"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":0.8064032196998596},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7000614404678345},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5561493635177612},{"id":"https://openalex.org/keywords/syntax","display_name":"Syntax","score":0.5453575849533081},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.5417798757553101},{"id":"https://openalex.org/keywords/correctness","display_name":"Correctness","score":0.4613080322742462},{"id":"https://openalex.org/keywords/natural-language","display_name":"Natural language","score":0.4406958520412445},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3866994380950928},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.10113373398780823}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8064032196998596},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7000614404678345},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5561493635177612},{"id":"https://openalex.org/C60048249","wikidata":"https://www.wikidata.org/wiki/Q37437","display_name":"Syntax","level":2,"score":0.5453575849533081},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.5417798757553101},{"id":"https://openalex.org/C55439883","wikidata":"https://www.wikidata.org/wiki/Q360812","display_name":"Correctness","level":2,"score":0.4613080322742462},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.4406958520412445},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3866994380950928},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.10113373398780823}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2024.3397061","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1109/access.2024.3397061","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10520274.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:d3976e689758422fb7b7602f608332b0","is_oa":true,"landing_page_url":"https://doaj.org/article/d3976e689758422fb7b7602f608332b0","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 12, Pp 64360-64375 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2024.3397061","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1109/access.2024.3397061","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10520274.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.6100000143051147}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320306087","display_name":"Semiconductor Research Corporation","ror":"https://ror.org/047z4n946"},{"id":"https://openalex.org/F4320307102","display_name":"Intel Corporation","ror":"https://ror.org/01ek73717"},{"id":"https://openalex.org/F4320332180","display_name":"Defense Advanced Research Projects Agency","ror":"https://ror.org/02caytj08"},{"id":"https://openalex.org/F4320338295","display_name":"Army Research Laboratory","ror":"https://ror.org/011hc8f90"}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4396680818.pdf"},"referenced_works_count":50,"referenced_works":["https://openalex.org/W1903029394","https://openalex.org/W2005202058","https://openalex.org/W2077069816","https://openalex.org/W2105497548","https://openalex.org/W2118020555","https://openalex.org/W2136655611","https://openalex.org/W2148818729","https://openalex.org/W2187089797","https://openalex.org/W2197363001","https://openalex.org/W2579549467","https://openalex.org/W2599354622","https://openalex.org/W2888329843","https://openalex.org/W2888922637","https://openalex.org/W2891273344","https://openalex.org/W2896457183","https://openalex.org/W2962739339","https://openalex.org/W2963045681","https://openalex.org/W2975050087","https://openalex.org/W2996728628","https://openalex.org/W3034600949","https://openalex.org/W3035261420","https://openalex.org/W3166920165","https://openalex.org/W3170863103","https://openalex.org/W3203701986","https://openalex.org/W4205969993","https://openalex.org/W4280654467","https://openalex.org/W4288351520","https://openalex.org/W4299807969","https://openalex.org/W4307106676","https://openalex.org/W4313156423","https://openalex.org/W4382317531","https://openalex.org/W4385195017","https://openalex.org/W4385805156","https://openalex.org/W4386065890","https://openalex.org/W4388322158","https://openalex.org/W4390872231","https://openalex.org/W6620707391","https://openalex.org/W6684191040","https://openalex.org/W6712574313","https://openalex.org/W6748102297","https://openalex.org/W6751494907","https://openalex.org/W6751866786","https://openalex.org/W6752760542","https://openalex.org/W6754355446","https://openalex.org/W6755207826","https://openalex.org/W6757635932","https://openalex.org/W6767814141","https://openalex.org/W6791353385","https://openalex.org/W6796761347","https://openalex.org/W6803567076"],"related_works":["https://openalex.org/W3008339103","https://openalex.org/W1667647204","https://openalex.org/W2404647514","https://openalex.org/W4247536566","https://openalex.org/W4241418540","https://openalex.org/W2018477250","https://openalex.org/W2116246834","https://openalex.org/W4226226396","https://openalex.org/W3153750606","https://openalex.org/W4308854837"],"abstract_inverted_index":{"Syntax":[0],"is":[1,48,191,217],"usually":[2],"studied":[3],"in":[4,16,156,219],"the":[5,12,30,34,67,74,88,151,154,157,162,174,200,211,220,223,232,260],"realm":[6],"of":[7,14,33,69,78,90,104,254],"linguistics":[8],"and":[9,76,125,138,168,176,231,247,250,256,273],"refers":[10],"to":[11,45,50,82,86,92,120,184,202,208,264],"arrangement":[13],"words":[15,164],"a":[17,26,79,147],"sentence.":[18],"Similarly,":[19],"an":[20,101,171],"image":[21,35,158],"can":[22],"be":[23],"considered":[24],"as":[25,37,83,114,116],"visual":[27,40,140],"\u2018sentence\u2019,":[28],"with":[29,59,143,193,199,271],"semantic":[31],"parts":[32,178],"acting":[36],"\u2018words\u2019.":[38],"While":[39],"syntactic":[41,94,141,186],"understanding":[42,142],"occurs":[43],"naturally":[44],"humans,":[46],"it":[47],"interesting":[49],"explore":[51],"whether":[52],"deep":[53],"neural":[54,112],"networks":[55],"(DNNs)":[56],"are":[57,159,165,179,226,237],"equipped":[58],"such":[60,93],"reasoning.":[61],"To":[62,134],"that":[63,109,222],"end,":[64],"we":[65,99,107,145],"alter":[66],"syntax":[68],"natural":[70],"images":[71,225],"(e.g.":[72],"swapping":[73],"eye":[75],"nose":[77],"face),":[80],"referred":[81],"\u2018incorrect\u2019":[84],"images,":[85,127,198],"investigate":[87],"sensitivity":[89],"DNNs":[91,105],"anomaly.":[95],"Through":[96],"our":[97,214],"experiments,":[98],"discover":[100],"intriguing":[102],"property":[103],"where":[106],"observe":[108],"state-of-the-art":[110],"convolutional":[111],"networks,":[113],"well":[115,263],"vision":[117],"transformers,":[118],"fail":[119],"discriminate":[121],"between":[122],"syntactically":[123],"correct":[124,132,233],"incorrect":[126,224,235],"when":[128],"trained":[129,192],"on":[130,245,278],"only":[131,227],"ones.":[133],"counter":[135],"this":[136],"issue":[137],"enable":[139],"DNNs,":[144],"propose":[146],"three-stage":[148],"framework-":[149],"(i)":[150],"\u2018words\u2019":[152],"(or":[153],"sub-features)":[155],"detected,":[160],"(ii)":[161],"detected":[163],"sequentially":[166],"masked":[167,195],"reconstructed":[169,177],"using":[170],"autoencoder,":[172],"(iii)":[173],"original":[175],"compared":[180],"at":[181],"each":[182],"location":[183],"determine":[185],"correctness.":[187],"The":[188],"reconstruction":[189],"module":[190],"BERT-like":[194],"autoencoding":[196],"for":[197,240],"motivation":[201],"leverage":[203],"language":[204],"model":[205],"inspired":[206],"training":[207,277],"better":[209],"capture":[210],"syntax.":[212],"Note,":[213],"proposed":[215],"approach":[216,261],"unsupervised":[218],"sense":[221],"used":[228,239],"during":[229],"testing":[230],"versus":[234],"labels":[236],"never":[238],"training.":[241],"We":[242],"perform":[243],"experiments":[244],"CelebA,":[246],"AFHQ":[248,274],"datasets":[249],"obtain":[251],"classification":[252],"accuracy":[253],"92.10%,":[255],"90.89%,":[257],"respectively.":[258],"Notably,":[259],"generalizes":[262],"ImageNet":[265],"samples":[266],"which":[267],"share":[268],"common":[269],"classes":[270],"CelebA":[272],"without":[275],"explicitly":[276],"them.":[279]},"counts_by_year":[],"updated_date":"2025-12-26T23:08:49.675405","created_date":"2025-10-10T00:00:00"}
