{"id":"https://openalex.org/W4400905289","doi":"https://doi.org/10.1109/access.2024.3432670","title":"Transform Domain Learning for Image Recognition","display_name":"Transform Domain Learning for Image Recognition","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4400905289","doi":"https://doi.org/10.1109/access.2024.3432670"},"language":"en","primary_location":{"id":"doi:10.1109/access.2024.3432670","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1109/access.2024.3432670","pdf_url":null,"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":"http://dx.doi.org/10.1109/access.2024.3432670","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5013651388","display_name":"Dengtai Tan","orcid":"https://orcid.org/0000-0003-1567-9063"},"institutions":[{"id":"https://openalex.org/I4210125346","display_name":"Gansu Institute of Political Science and Law","ror":"https://ror.org/025km4h87","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210125346"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Dengtai Tan","raw_affiliation_strings":["School of Artificial Intelligence, Gansu University of Political Science and Law, Lanzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-1567-9063","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Gansu University of Political Science and Law, Lanzhou, China","institution_ids":["https://openalex.org/I4210125346"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084997508","display_name":"Jinlong Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I4210125346","display_name":"Gansu Institute of Political Science and Law","ror":"https://ror.org/025km4h87","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210125346"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinlong Zhao","raw_affiliation_strings":["School of Artificial Intelligence, Gansu University of Political Science and Law, Lanzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Gansu University of Political Science and Law, Lanzhou, China","institution_ids":["https://openalex.org/I4210125346"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100615081","display_name":"Shichao Li","orcid":"https://orcid.org/0000-0001-6858-5031"},"institutions":[{"id":"https://openalex.org/I5343935","display_name":"Guilin University of Electronic Technology","ror":"https://ror.org/05arjae42","country_code":"CN","type":"education","lineage":["https://openalex.org/I5343935"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shichao Li","raw_affiliation_strings":["School of Information and Communication, Guilin University of Electronic Technology, Guilin, China"],"raw_orcid":"https://orcid.org/0000-0001-6858-5031","affiliations":[{"raw_affiliation_string":"School of Information and Communication, Guilin University of Electronic Technology, Guilin, China","institution_ids":["https://openalex.org/I5343935"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5013651388"],"corresponding_institution_ids":["https://openalex.org/I4210125346"],"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":0.09940843,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"12","issue":null,"first_page":"101851","last_page":"101864"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9998999834060669,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9998999834060669,"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":0.9991999864578247,"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":0.9991000294685364,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.8059308528900146},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.794019877910614},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7928770780563354},{"id":"https://openalex.org/keywords/transformation","display_name":"Transformation (genetics)","score":0.6284724473953247},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6258506178855896},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.5250858068466187},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5076116323471069},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4959166944026947},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4934145510196686},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.4258008599281311},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11403408646583557}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.8059308528900146},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.794019877910614},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7928770780563354},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.6284724473953247},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6258506178855896},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.5250858068466187},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5076116323471069},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4959166944026947},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4934145510196686},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.4258008599281311},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11403408646583557},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2024.3432670","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1109/access.2024.3432670","pdf_url":null,"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:d69680d3989e4eef9e1c7f13ce2277c2","is_oa":true,"landing_page_url":"https://doaj.org/article/d69680d3989e4eef9e1c7f13ce2277c2","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 12, Pp 101851-101864 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2024.3432670","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1109/access.2024.3432670","pdf_url":null,"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":[],"awards":[{"id":"https://openalex.org/G1251179664","display_name":null,"funder_award_id":"GZF2023XZD19","funder_id":"https://openalex.org/F4320325175","funder_display_name":"China University of Political Science and Law"},{"id":"https://openalex.org/G509906617","display_name":null,"funder_award_id":"2022A-095","funder_id":"https://openalex.org/F4320328887","funder_display_name":"University Project of Gansu Province"}],"funders":[{"id":"https://openalex.org/F4320325175","display_name":"China University of Political Science and Law","ror":"https://ror.org/00e49gy82"},{"id":"https://openalex.org/F4320328887","display_name":"University Project of Gansu Province","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W1522734439","https://openalex.org/W1686810756","https://openalex.org/W2097117768","https://openalex.org/W2108598243","https://openalex.org/W2115733720","https://openalex.org/W2194775991","https://openalex.org/W2883429621","https://openalex.org/W2900859886","https://openalex.org/W2962934715","https://openalex.org/W2963155035","https://openalex.org/W2963524571","https://openalex.org/W2963820951","https://openalex.org/W2981548405","https://openalex.org/W2984287396","https://openalex.org/W3034771037","https://openalex.org/W3035865126","https://openalex.org/W3099895171","https://openalex.org/W3118608800","https://openalex.org/W3133794206","https://openalex.org/W3136416617","https://openalex.org/W3142722142","https://openalex.org/W3186706259","https://openalex.org/W3206354200","https://openalex.org/W3213366661","https://openalex.org/W4214612132","https://openalex.org/W4214634256","https://openalex.org/W4225755514","https://openalex.org/W4226110133","https://openalex.org/W4253964759","https://openalex.org/W4285190850","https://openalex.org/W4297697565","https://openalex.org/W4309435465","https://openalex.org/W4366208220","https://openalex.org/W4385245566","https://openalex.org/W4386076398","https://openalex.org/W4390788035","https://openalex.org/W4391855083","https://openalex.org/W6637373629","https://openalex.org/W6653066577","https://openalex.org/W6754427640","https://openalex.org/W6787972765","https://openalex.org/W6802549816","https://openalex.org/W6803602085","https://openalex.org/W6810411996","https://openalex.org/W6810471921","https://openalex.org/W6851800889"],"related_works":["https://openalex.org/W4391621807","https://openalex.org/W2900584650","https://openalex.org/W2911497689","https://openalex.org/W2952813363","https://openalex.org/W2963346891","https://openalex.org/W4360783045","https://openalex.org/W2770149305","https://openalex.org/W3167930666","https://openalex.org/W3014952856","https://openalex.org/W3010730661"],"abstract_inverted_index":{"Image":[0],"and":[1,38,125,168,175,182,199],"video":[2,20,39,59,169,177,217],"classification":[3,223],"are":[4,16,29,180,185],"distinct":[5],"tasks":[6,165],"in":[7,190],"computer":[8],"vision.":[9],"Three-dimensional":[10],"convolutional":[11,24],"neural":[12,25],"networks":[13,26],"(3D":[14],"CNNs)":[15,28],"commonly":[17],"employed":[18],"for":[19,32,54,78,84],"classification,":[21,170],"while":[22],"two-dimensional":[23],"(2D":[27],"more":[30],"suitable":[31],"image":[33,37,55,90,167,172,222],"classification.":[34],"To":[35,162],"enable":[36],"recognition":[40,56,60,206],"to":[41,122,149,187,220],"adopt":[42],"the":[43,58,71,85,93,103,106,140,152,160,164,171,176,191,204,216,221,228],"same":[44,205],"network-3D":[45],"CNNs,":[46,151],"we":[47],"propose":[48],"a":[49,110],"transform":[50,65,192],"domain":[51,66],"learning":[52,67],"approach":[53],"utilizing":[57],"model":[61,219],"3D":[62,79,116,142,183],"CNNs.":[63],"The":[64,114,127,194],"not":[68,158],"only":[69],"permits":[70],"use":[72],"of":[73,87,166],"RGB":[74],"images":[75,98,124,189],"as":[76,139],"input":[77,86],"CNNs":[80,117,143,184],"but":[81],"also":[82],"allows":[83],"orthogonally":[88],"transformed":[89,97],"sequences":[91],"into":[92,102],"networks.":[94],"Furthermore,":[95],"randomly":[96],"can":[99,118,144,210,225],"be":[100,119,211],"fed":[101],"networks,":[104],"where":[105],"random":[107,135],"transformation":[108,133,136,156],"is":[109,137],"customized":[111],"arbitrary":[112],"transformation.":[113],"standard":[115],"seamlessly":[120],"applied":[121],"both":[123],"videos.":[126],"experiments":[128],"show":[129],"that":[130,197,213],"whether":[131],"orthogonal":[132,155],"or":[134],"used":[138,186],"input,":[141],"effectively":[145],"classify":[146],"images.":[147],"Compared":[148],"2D":[150],"data":[153],"after":[154],"does":[157],"reduce":[159],"accuracy.":[161],"unify":[163],"dataset":[173,178],"Caltech101":[174],"UCF101":[179],"mixed,":[181],"recognize":[188],"domain.":[193],"results":[195],"illustrate":[196],"mixed":[198],"individual":[200],"training":[201],"produce":[202],"almost":[203],"effect.":[207],"Additionally,":[208],"it":[209],"observed":[212],"directly":[214],"transferring":[215],"pre-training":[218],"task":[224],"significantly":[226],"enhance":[227],"performance.":[229]},"counts_by_year":[],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}