{"id":"https://openalex.org/W4200465820","doi":"https://doi.org/10.1088/1742-6596/2083/4/042027","title":"Study on a visual coder acceleration algorithm for image classification applying dynamic scaling training techniques","display_name":"Study on a visual coder acceleration algorithm for image classification applying dynamic scaling training techniques","publication_year":2021,"publication_date":"2021-11-01","ids":{"openalex":"https://openalex.org/W4200465820","doi":"https://doi.org/10.1088/1742-6596/2083/4/042027"},"language":"en","primary_location":{"id":"doi:10.1088/1742-6596/2083/4/042027","doi":"https://doi.org/10.1088/1742-6596/2083/4/042027","is_oa":true,"landing_page_url":"https://doi.org/10.1088/1742-6596/2083/4/042027","pdf_url":"https://iopscience.iop.org/article/10.1088/1742-6596/2083/4/042027/pdf","source":{"id":"https://openalex.org/S4210187594","display_name":"Journal of Physics Conference Series","issn_l":"1742-6588","issn":["1742-6588","1742-6596"],"is_oa":true,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","jufo-1","norway-1","poland-40","vabb-shw"],"host_organization":"https://openalex.org/P4310320083","host_organization_name":"IOP Publishing","host_organization_lineage":["https://openalex.org/P4310320083","https://openalex.org/P4310311669"],"host_organization_lineage_names":["IOP Publishing","Institute of Physics"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Physics: Conference Series","raw_type":"journal-article"},"parent_works":[],"lineage":["https://openalex.org/W4200465820"],"child_works_count":0,"type":"conference-paper","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://iopscience.iop.org/article/10.1088/1742-6596/2083/4/042027/pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5053424863","display_name":"Junliang Huo","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I101479585","display_name":"South China Agricultural University","ror":"https://ror.org/05v9jqt67","country_code":"CN","type":"education","lineage":["https://openalex.org/I101479585"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junliang Huo","raw_affiliation_strings":["College of Engineering, South China Agricultural University, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Engineering, South China Agricultural University, Guangzhou, China","institution_ids":["https://openalex.org/I101479585"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007421340","display_name":"Jiankun Ling","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I101479585","display_name":"South China Agricultural University","ror":"https://ror.org/05v9jqt67","country_code":"CN","type":"education","lineage":["https://openalex.org/I101479585"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiankun Ling","raw_affiliation_strings":["College of Engineering, South China Agricultural University, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Engineering, South China Agricultural University, Guangzhou, China","institution_ids":["https://openalex.org/I101479585"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I101479585"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"2083","issue":"4","first_page":"042027","last_page":"042027"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9976000189781189,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9976000189781189,"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":0.0020000000949949026,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.0,"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/vision-transformer","display_name":"vision transformer","score":0.6029999852180481},{"id":"https://openalex.org/keywords/deit","display_name":"DeiT","score":0.8270000219345093},{"id":"https://openalex.org/keywords/dynamic-scaling","display_name":"dynamic scaling","score":0.7649999856948853},{"id":"https://openalex.org/keywords/image-classification","display_name":"image classification","score":0.75},{"id":"https://openalex.org/keywords/model-compression","display_name":"model compression","score":0.5770000219345093},{"id":"https://openalex.org/keywords/autonomous-vehicles","display_name":"autonomous vehicles","score":0.6050000190734863},{"id":"https://openalex.org/keywords/cifar-100","display_name":"CIFAR-100","score":0.7440000176429749}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7834558486938477},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7182135581970215},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5770215392112732},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.4839673340320587},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4617012143135071},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4504642188549042},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.4339144825935364},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.42787501215934753},{"id":"https://openalex.org/C186633575","wikidata":"https://www.wikidata.org/wiki/Q845060","display_name":"Maxima and minima","level":2,"score":0.41657760739326477},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.40684908628463745},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08467534184455872},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.05978882312774658},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","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":1,"locations":[{"id":"doi:10.1088/1742-6596/2083/4/042027","doi":"https://doi.org/10.1088/1742-6596/2083/4/042027","is_oa":true,"landing_page_url":"https://doi.org/10.1088/1742-6596/2083/4/042027","pdf_url":"https://iopscience.iop.org/article/10.1088/1742-6596/2083/4/042027/pdf","source":{"id":"https://openalex.org/S4210187594","display_name":"Journal of Physics Conference Series","issn_l":"1742-6588","issn":["1742-6588","1742-6596"],"is_oa":true,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","jufo-1","norway-1","poland-40","vabb-shw"],"host_organization":"https://openalex.org/P4310320083","host_organization_name":"IOP Publishing","host_organization_lineage":["https://openalex.org/P4310320083","https://openalex.org/P4310311669"],"host_organization_lineage_names":["IOP Publishing","Institute of Physics"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Physics: Conference Series","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1088/1742-6596/2083/4/042027","doi":"https://doi.org/10.1088/1742-6596/2083/4/042027","is_oa":true,"landing_page_url":"https://doi.org/10.1088/1742-6596/2083/4/042027","pdf_url":"https://iopscience.iop.org/article/10.1088/1742-6596/2083/4/042027/pdf","source":{"id":"https://openalex.org/S4210187594","display_name":"Journal of Physics Conference Series","issn_l":"1742-6588","issn":["1742-6588","1742-6596"],"is_oa":true,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","jufo-1","norway-1","poland-40","vabb-shw"],"host_organization":"https://openalex.org/P4310320083","host_organization_name":"IOP Publishing","host_organization_lineage":["https://openalex.org/P4310320083","https://openalex.org/P4310311669"],"host_organization_lineage_names":["IOP Publishing","Institute of Physics"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Physics: Conference Series","raw_type":"journal-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4200465820.pdf","grobid_xml":"https://content.openalex.org/works/W4200465820.grobid-xml"},"referenced_works_count":4,"referenced_works":["https://openalex.org/W2747909401","https://openalex.org/W2769312802","https://openalex.org/W3035030897","https://openalex.org/W3157506437"],"related_works":["https://openalex.org/W4225825436","https://openalex.org/W4415820794","https://openalex.org/W4214633470","https://openalex.org/W4386027557","https://openalex.org/W4379116387","https://openalex.org/W4225365588","https://openalex.org/W4404838659","https://openalex.org/W4416874193","https://openalex.org/W7171549041"],"abstract_inverted_index":{"Abstract":[0],"Nowadays,":[1],"image":[2,135,155],"classification":[3,136,156],"techniques":[4,123,127],"are":[5,26,139],"used":[6,19,27,49,76],"in":[7,33,77,82,95,103],"the":[8,37,42,52,87,92,98,142,146,149,152],"field":[9],"of":[10,29,69,151],"autonomous":[11],"vehicles,":[12],"and":[13,21,40,90,105,112,124,128,145],"Convolutional":[14],"Neural":[15],"Network":[16],"(CNN)":[17],"is":[18,48,75,100],"extensively,":[20],"Vision":[22],"Transformer":[23],"(ViT)":[24],"networks":[25,32],"instead":[28],"deep":[30,53],"convolutional":[31,54],"order":[34,83],"to":[35,50,63,84,131,134],"compress":[36],"network":[38,47,99],"size":[39,104],"improve":[41],"model":[43],"accuracy.":[44],"The":[45],"ViT":[46,58],"replace":[51],"network.":[55],"Since":[56],"training":[57,106],"requires":[59],"a":[60,67],"large":[61],"dataset":[62],"have":[64],"sufficient":[65],"accuracy,":[66],"variant":[68],"ViT,":[70],"Data-Efficient":[71],"Image":[72],"Transformers":[73],"(DEIT),":[74],"this":[78,116],"paper.":[79],"In":[80,115],"addition,":[81],"greatly":[85],"reduce":[86],"computing":[88,93],"memory":[89],"shorten":[91],"time":[94],"practical":[96],"use,":[97],"flexibly":[101],"scaled":[102],"speed":[107],"by":[108],"both":[109],"adaptive":[110,113,122,126],"width":[111,121],"depth.":[114],"paper,":[117],"we":[118],"introduce":[119],"DEIT,":[120],"depth":[125],"combine":[129],"them":[130],"be":[132],"applied":[133],"examples.":[137],"Experiments":[138],"conducted":[140],"on":[141,154],"Cifar100":[143],"dataset,":[144],"experiments":[147],"demonstrate":[148],"superiority":[150],"algorithm":[153],"scenarios.":[157]},"counts_by_year":[],"updated_date":"2026-11-14T11:04:58.165337","created_date":"2021-12-31T00:00:00"}