{"id":"https://openalex.org/W3185035581","doi":null,"title":"A Comparison of Deep Learning Classification Methods on Small-scale Image Data set: from Convolutional Neural Networks to Visual Transformers.","display_name":"A Comparison of Deep Learning Classification Methods on Small-scale Image Data set: from Convolutional Neural Networks to Visual Transformers.","publication_year":2021,"publication_date":"2021-07-16","ids":{"openalex":"https://openalex.org/W3185035581","mag":"3185035581"},"language":"en","primary_location":{"id":"mag:3185035581","doi":null,"is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/2107.07699","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://export.arxiv.org/pdf/2107.07699","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101645108","display_name":"Peng Zhao","orcid":"https://orcid.org/0000-0003-4668-1852","observed_orcids":["https://orcid.org/0000-0003-4668-1852"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Peng Zhao","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0003-4668-1852","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100369916","display_name":"Chen Li","orcid":"https://orcid.org/0000-0003-1545-8885","observed_orcids":["https://orcid.org/0000-0003-1545-8885","https://orcid.org/0009-0008-3134-7572"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen Li","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0003-1545-8885","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075100287","display_name":"Md Mamunur Rahaman","orcid":"https://orcid.org/0000-0003-2268-2092","observed_orcids":["https://orcid.org/0000-0003-2268-2092"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Md Mamunur Rahaman","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0003-2268-2092","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084965453","display_name":"Hechen Yang","orcid":"https://orcid.org/0000-0001-5863-8224","observed_orcids":["https://orcid.org/0000-0001-5863-8224"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hechen Yang","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0001-5863-8224","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100648261","display_name":"Tao Jiang","orcid":"https://orcid.org/0000-0001-8296-3027","observed_orcids":["https://orcid.org/0000-0001-8296-3027"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tao Jiang","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0001-8296-3027","affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5037990310","display_name":"Marcin Grzegorzek","orcid":"https://orcid.org/0000-0003-4877-8287","observed_orcids":["https://orcid.org/0000-0003-4877-8287"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Marcin Grzegorzek","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0003-4877-8287","affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9839000105857849,"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":0.9839000105857849,"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":0.015399999916553497,"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":9.999999747378752e-05,"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/image-classification","display_name":"image classification","score":0.878000020980835},{"id":"https://openalex.org/keywords/small-datasets","display_name":"small datasets","score":0.7889999747276306},{"id":"https://openalex.org/keywords/convolutional-neural-networks","display_name":"convolutional neural networks","score":0.9860000014305115},{"id":"https://openalex.org/keywords/vision-transformer","display_name":"vision transformer","score":0.8220000267028809},{"id":"https://openalex.org/keywords/model-comparison","display_name":"model comparison","score":0.7749999761581421},{"id":"https://openalex.org/keywords/data-scarcity","display_name":"data scarcity","score":0.5080000162124634},{"id":"https://openalex.org/keywords/transfer-learning","display_name":"transfer learning","score":0.6010000109672546}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7895065546035767},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.712101936340332},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.6789935231208801},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6726142168045044},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.63811194896698},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5435532927513123},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.5013642311096191},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.48233315348625183},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4766741096973419},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4413708448410034},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.43107306957244873},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4162783920764923},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3553500771522522},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.13021886348724365},{"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/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"mag:3185035581","doi":null,"is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/2107.07699","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null}],"best_oa_location":{"id":"mag:3185035581","doi":null,"is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/2107.07699","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W46659105","https://openalex.org/W1686810756","https://openalex.org/W2097117768","https://openalex.org/W2163605009","https://openalex.org/W2183341477","https://openalex.org/W2194775991","https://openalex.org/W2271192305","https://openalex.org/W2311523351","https://openalex.org/W2336238079","https://openalex.org/W2398921440","https://openalex.org/W2417429787","https://openalex.org/W2531409750","https://openalex.org/W2744043610","https://openalex.org/W2770456481","https://openalex.org/W2802802696","https://openalex.org/W2883780447","https://openalex.org/W2887280559","https://openalex.org/W2896811665","https://openalex.org/W2905230381","https://openalex.org/W2964350391","https://openalex.org/W2982127434","https://openalex.org/W2994801906","https://openalex.org/W3011667710","https://openalex.org/W3046220160","https://openalex.org/W3094502228","https://openalex.org/W3116489684","https://openalex.org/W3121523901","https://openalex.org/W3122484828","https://openalex.org/W3130012542","https://openalex.org/W3135310702","https://openalex.org/W3143802587","https://openalex.org/W3187418919"],"related_works":["https://openalex.org/W3167724546","https://openalex.org/W4214808100","https://openalex.org/W7118866282","https://openalex.org/W4391307612","https://openalex.org/W2977095415","https://openalex.org/W4399392974","https://openalex.org/W2417429787","https://openalex.org/W2994801906","https://openalex.org/W7220006009","https://openalex.org/W4380563926"],"abstract_inverted_index":{"In":[0],"recent":[1],"years,":[2],"deep":[3,90],"learning":[4,91],"has":[5],"made":[6],"brilliant":[7],"achievements":[8],"in":[9,77],"image":[10,13],"classification.":[11],"However,":[12],"classification":[14,49],"of":[15,34,44,58,74,85],"small":[16,45,65],"datasets":[17,66],"is":[18,93],"still":[19],"not":[20],"obtained":[21],"good":[22],"research":[23],"results.":[24],"This":[25],"article":[26],"first":[27],"briefly":[28],"explains":[29],"the":[30,42,51,64,72,78,83,88,97],"application":[31,99],"and":[32,38,50,71],"characteristics":[33],"convolutional":[35],"neural":[36],"networks":[37],"visual":[39],"transformers.":[40],"Meanwhile,":[41],"influence":[43],"data":[46],"set":[47],"on":[48,63],"solution":[52],"are":[53,60,80],"introduced.":[54],"Then":[55],"a":[56],"series":[57],"experiments":[59,79],"carried":[61],"out":[62],"by":[67],"using":[68],"various":[69],"models,":[70],"problems":[73],"some":[75],"models":[76],"discussed.":[81],"Through":[82],"comparison":[84],"experimental":[86],"results,":[87],"recommended":[89],"model":[92,98],"given":[94],"according":[95],"to":[96],"environment.":[100],"Finally,":[101],"we":[102],"give":[103],"directions":[104],"for":[105],"future":[106],"work.":[107]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2}],"updated_date":"2026-10-29T09:56:32.521200","created_date":"2021-08-02T00:00:00"}