{"id":"https://openalex.org/W4417258039","doi":"https://doi.org/10.48550/arxiv.2506.08956","title":"Data Augmentation For Small Object using Fast AutoAugment","display_name":"Data Augmentation For Small Object using Fast AutoAugment","publication_year":2025,"publication_date":"2025-06-10","ids":{"openalex":"https://openalex.org/W4417258039","doi":"https://doi.org/10.48550/arxiv.2506.08956"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2506.08956","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2506.08956","pdf_url":"https://arxiv.org/pdf/2506.08956","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2506.08956","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Yoon, DaeEun","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yoon, DaeEun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Kim, Semin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kim, Semin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Yoo, SangWook","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yoo, SangWook","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5100724655","display_name":"Jongha Lee","orcid":"https://orcid.org/0000-0002-1568-6733"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lee, Jongha","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"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":0.9424999952316284,"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":0.9424999952316284,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.008799999952316284,"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/T12389","display_name":"Infrared Target Detection Methodologies","score":0.004800000227987766,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.6887999773025513},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.6327999830245972},{"id":"https://openalex.org/keywords/small-data","display_name":"Small data","score":0.3790000081062317},{"id":"https://openalex.org/keywords/degradation","display_name":"Degradation (telecommunications)","score":0.3073999881744385},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.2937000095844269}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7379999756813049},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.6887999773025513},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.6327999830245972},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5914000272750854},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5662999749183655},{"id":"https://openalex.org/C2779280203","wikidata":"https://www.wikidata.org/wiki/Q17121211","display_name":"Small data","level":2,"score":0.3790000081062317},{"id":"https://openalex.org/C2779679103","wikidata":"https://www.wikidata.org/wiki/Q5251805","display_name":"Degradation (telecommunications)","level":2,"score":0.3073999881744385},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.2937000095844269},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.2630999982357025},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.24889999628067017}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2506.08956","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2506.08956","pdf_url":"https://arxiv.org/pdf/2506.08956","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2506.08956","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2506.08956","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2506.08956","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2506.08956","pdf_url":"https://arxiv.org/pdf/2506.08956","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"In":[0],"recent":[1],"years,":[2],"there":[3],"has":[4],"been":[5],"tremendous":[6],"progress":[7],"in":[8,42],"object":[9],"detection":[10,17,48],"performance.":[11],"However,":[12],"despite":[13],"these":[14],"advances,":[15],"the":[16,36,47,90],"performance":[18,49,87],"for":[19,50],"small":[20,31,51,80],"objects":[21,32],"is":[22,33],"significantly":[23],"inferior":[24],"to":[25],"that":[26,74],"of":[27,35],"large":[28],"objects.":[29],"Detecting":[30],"one":[34],"most":[37],"challenging":[38],"and":[39,82],"important":[40],"problems":[41],"computer":[43],"vision.":[44],"To":[45],"improve":[46],"objects,":[52,81],"we":[53,67,83],"propose":[54],"an":[55],"optimal":[56,71],"data":[57],"augmentation":[58,72],"method":[59],"using":[60],"Fast":[61],"AutoAugment.":[62],"Through":[63],"our":[64],"proposed":[65],"method,":[66],"can":[68,75],"quickly":[69],"find":[70],"policies":[73],"overcome":[76],"degradation":[77],"when":[78],"detecting":[79],"achieve":[84],"a":[85],"20%":[86],"improvement":[88],"on":[89],"DOTA":[91],"dataset.":[92]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
