{"id":"https://openalex.org/W4296362984","doi":"https://doi.org/10.3390/s22187020","title":"Detecting Human Actions in Drone Images Using YoloV5 and Stochastic Gradient Boosting","display_name":"Detecting Human Actions in Drone Images Using YoloV5 and Stochastic Gradient Boosting","publication_year":2022,"publication_date":"2022-09-16","ids":{"openalex":"https://openalex.org/W4296362984","doi":"https://doi.org/10.3390/s22187020","pmid":"https://pubmed.ncbi.nlm.nih.gov/36146369"},"language":"en","primary_location":{"id":"doi:10.3390/s22187020","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s22187020","pdf_url":"https://www.mdpi.com/1424-8220/22/18/7020/pdf?version=1663323097","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/22/18/7020/pdf?version=1663323097","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5011693212","display_name":"Tasweer Ahmad","orcid":null},"institutions":[{"id":"https://openalex.org/I16076960","display_name":"COMSATS University Islamabad","ror":"https://ror.org/00nqqvk19","country_code":"PK","type":"education","lineage":["https://openalex.org/I16076960"]}],"countries":["PK"],"is_corresponding":true,"raw_author_name":"Tasweer Ahmad","raw_affiliation_strings":["Department of Electrical and Computer Engineering, COMSATS University Islamabad, Islamabad 45550, Pakistan"],"raw_orcid":"https://orcid.org/0000-0002-8108-7915","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, COMSATS University Islamabad, Islamabad 45550, Pakistan","institution_ids":["https://openalex.org/I16076960"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076006850","display_name":"Marc Cavazza","orcid":"https://orcid.org/0000-0001-6113-9696"},"institutions":[{"id":"https://openalex.org/I184597095","display_name":"National Institute of Informatics","ror":"https://ror.org/04ksd4g47","country_code":"JP","type":"facility","lineage":["https://openalex.org/I1319490839","https://openalex.org/I184597095","https://openalex.org/I4210158934"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Marc Cavazza","raw_affiliation_strings":["National Institute of Informatics, Tokyo 101-8430, Japan"],"raw_orcid":"https://orcid.org/0000-0001-6113-9696","affiliations":[{"raw_affiliation_string":"National Institute of Informatics, Tokyo 101-8430, Japan","institution_ids":["https://openalex.org/I184597095"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074059447","display_name":"Yutaka Matsuo","orcid":"https://orcid.org/0000-0002-2070-4393"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yutaka Matsuo","raw_affiliation_strings":["Department of Engineering, The University of Tokyo, Tokyo 113-8654, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Engineering, The University of Tokyo, Tokyo 113-8654, Japan","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074421055","display_name":"Helmut Prendinger","orcid":"https://orcid.org/0000-0003-4654-9835"},"institutions":[{"id":"https://openalex.org/I184597095","display_name":"National Institute of Informatics","ror":"https://ror.org/04ksd4g47","country_code":"JP","type":"facility","lineage":["https://openalex.org/I1319490839","https://openalex.org/I184597095","https://openalex.org/I4210158934"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Helmut Prendinger","raw_affiliation_strings":["National Institute of Informatics, Tokyo 101-8430, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Institute of Informatics, Tokyo 101-8430, Japan","institution_ids":["https://openalex.org/I184597095"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5011693212"],"corresponding_institution_ids":["https://openalex.org/I16076960"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2673},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2673},"fwci":3.2393,"has_fulltext":false,"cited_by_count":43,"citation_normalized_percentile":{"value":0.93687176,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"22","issue":"18","first_page":"7020","last_page":"7020"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9995999932289124,"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":0.9995999932289124,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9987999796867371,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.996999979019165,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7902772426605225},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7512761354446411},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.7041323184967041},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.6006088852882385},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5731610059738159},{"id":"https://openalex.org/keywords/drone","display_name":"Drone","score":0.570808470249176},{"id":"https://openalex.org/keywords/cognitive-neuroscience-of-visual-object-recognition","display_name":"Cognitive neuroscience of visual object recognition","score":0.5680594444274902},{"id":"https://openalex.org/keywords/gradient-boosting","display_name":"Gradient boosting","score":0.5064090490341187},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4968710243701935},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.42873457074165344},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4282371401786804},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.42481040954589844},{"id":"https://openalex.org/keywords/action-recognition","display_name":"Action recognition","score":0.41398119926452637},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.33164167404174805},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.3184973895549774},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.21366816759109497}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7902772426605225},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7512761354446411},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.7041323184967041},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.6006088852882385},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5731610059738159},{"id":"https://openalex.org/C59519942","wikidata":"https://www.wikidata.org/wiki/Q650665","display_name":"Drone","level":2,"score":0.570808470249176},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.5680594444274902},{"id":"https://openalex.org/C70153297","wikidata":"https://www.wikidata.org/wiki/Q5591907","display_name":"Gradient boosting","level":3,"score":0.5064090490341187},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4968710243701935},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.42873457074165344},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4282371401786804},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.42481040954589844},{"id":"https://openalex.org/C2987834672","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Action recognition","level":3,"score":0.41398119926452637},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.33164167404174805},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3184973895549774},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.21366816759109497},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000088722","descriptor_name":"Unmanned Aerial Devices","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000088722","descriptor_name":"Unmanned Aerial Devices","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000088722","descriptor_name":"Unmanned Aerial Devices","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006802","descriptor_name":"Human Activities","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006802","descriptor_name":"Human Activities","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006802","descriptor_name":"Human Activities","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":5,"locations":[{"id":"doi:10.3390/s22187020","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s22187020","pdf_url":"https://www.mdpi.com/1424-8220/22/18/7020/pdf?version=1663323097","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},{"id":"pmid:36146369","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/36146369","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:doaj.org/article:f433cea8272845659adbd922d6e78de7","is_oa":true,"landing_page_url":"https://doaj.org/article/f433cea8272845659adbd922d6e78de7","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":"Sensors, Vol 22, Iss 18, p 7020 (2022)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1424-8220/22/18/7020/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/s22187020","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors; Volume 22; Issue 18; Pages: 7020","raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:9503017","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9503017","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors (Basel)","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/s22187020","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s22187020","pdf_url":"https://www.mdpi.com/1424-8220/22/18/7020/pdf?version=1663323097","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4296362984.pdf"},"referenced_works_count":63,"referenced_works":["https://openalex.org/W1441581489","https://openalex.org/W1536680647","https://openalex.org/W1678356000","https://openalex.org/W2019660985","https://openalex.org/W2034482269","https://openalex.org/W2070493638","https://openalex.org/W2097342496","https://openalex.org/W2102605133","https://openalex.org/W2105101328","https://openalex.org/W2129018774","https://openalex.org/W2139857301","https://openalex.org/W2149705965","https://openalex.org/W2172207578","https://openalex.org/W2179401333","https://openalex.org/W2193145675","https://openalex.org/W2194775991","https://openalex.org/W2295598076","https://openalex.org/W2461621749","https://openalex.org/W2549139847","https://openalex.org/W2565639579","https://openalex.org/W2570343428","https://openalex.org/W2583194072","https://openalex.org/W2613718673","https://openalex.org/W2613763509","https://openalex.org/W2625286981","https://openalex.org/W2666547004","https://openalex.org/W2883734140","https://openalex.org/W2884256296","https://openalex.org/W2899607431","https://openalex.org/W2901506610","https://openalex.org/W2905037335","https://openalex.org/W2911055311","https://openalex.org/W2911211067","https://openalex.org/W2944557626","https://openalex.org/W2945676084","https://openalex.org/W2946948417","https://openalex.org/W2963037989","https://openalex.org/W2963163009","https://openalex.org/W2963268857","https://openalex.org/W2963351448","https://openalex.org/W2963446712","https://openalex.org/W2963524571","https://openalex.org/W2963857746","https://openalex.org/W2964444661","https://openalex.org/W2970176295","https://openalex.org/W2970977083","https://openalex.org/W2990949296","https://openalex.org/W3009803092","https://openalex.org/W3016641475","https://openalex.org/W3034971973","https://openalex.org/W3036570594","https://openalex.org/W3088102655","https://openalex.org/W3092151103","https://openalex.org/W3105022516","https://openalex.org/W3106250896","https://openalex.org/W3134822545","https://openalex.org/W3134909472","https://openalex.org/W3160967194","https://openalex.org/W3173730467","https://openalex.org/W4285819743","https://openalex.org/W4286212714","https://openalex.org/W6756040250","https://openalex.org/W6762615656"],"related_works":["https://openalex.org/W4229448053","https://openalex.org/W4247925126","https://openalex.org/W4327774218","https://openalex.org/W2059768187","https://openalex.org/W4312858960","https://openalex.org/W4386036939","https://openalex.org/W4379143281","https://openalex.org/W2605096541","https://openalex.org/W3200286695","https://openalex.org/W2507540959"],"abstract_inverted_index":{"Human":[0],"action":[1,75,87,104,133],"recognition":[2,76,88,126,154],"and":[3,36,49,51,71,127,151,179,205,219],"detection":[4],"from":[5,31],"unmanned":[6],"aerial":[7],"vehicles":[8],"(UAVs),":[9],"or":[10,117],"drones,":[11],"has":[12],"emerged":[13],"as":[14,114],"a":[15,40,90,122,140,149,158,213],"popular":[16],"technical":[17],"challenge":[18],"in":[19,65,233],"recent":[20],"years,":[21],"since":[22],"it":[23],"is":[24,107,146,161,212],"related":[25],"to":[26,34,46,130,147,163,195,226],"many":[27],"use":[28,148],"case":[29],"scenarios":[30],"environmental":[32],"monitoring":[33],"search":[35],"rescue.":[37],"It":[38],"faces":[39],"number":[41],"of":[42,124,166,177,183,215,223,229,235],"difficulties":[43],"mainly":[44],"due":[45],"image":[47,59,110],"acquisition":[48,111],"contents,":[50],"processing":[52],"constraints.":[53],"Since":[54],"drones'":[55],"flying":[56],"conditions":[57],"constrain":[58],"acquisition,":[60],"human":[61],"subjects":[62],"may":[63],"appear":[64],"images":[66],"at":[67],"variable":[68,167],"scales,":[69],"orientations,":[70],"occlusion,":[72],"which":[73,199],"makes":[74],"more":[77],"difficult.":[78],"We":[79,120],"explore":[80],"low-resource":[81],"methods":[82],"for":[83,103,109],"ML":[84],"(machine":[85],"learning)-based":[86],"using":[89],"previously":[91],"collected":[92],"real-world":[93],"dataset":[94,99,232],"(the":[95],"\"Okutama-Action\"":[96],"dataset).":[97],"This":[98],"contains":[100],"representative":[101],"situations":[102],"recognition,":[105],"yet":[106],"controlled":[108],"parameters":[112],"such":[113],"camera":[115],"angle":[116],"flight":[118],"altitude.":[119],"investigate":[121],"combination":[123],"object":[125,153,203],"classifier":[128,159],"techniques":[129],"support":[131],"single-image":[132],"identification.":[134],"Our":[135,189],"architecture":[136],"integrates":[137],"YoloV5":[138,178,217],"with":[139,157],"gradient":[141],"boosting":[142],"classifier;":[143],"the":[144,181,196,220,227,230],"rationale":[145],"scalable":[150],"efficient":[152],"system":[155],"coupled":[156],"that":[160,210],"able":[162],"incorporate":[164],"samples":[165],"difficulty.":[168],"In":[169],"an":[170],"ablation":[171],"study,":[172],"we":[173,208],"test":[174],"different":[175],"architectures":[176,193],"evaluate":[180],"performance":[182,218],"our":[184,224],"method":[185],"on":[186],"Okutama-Action":[187],"dataset.":[188],"approach":[190],"outperformed":[191],"previous":[192],"applied":[194],"Okutama":[197,231],"dataset,":[198],"differed":[200],"by":[201],"their":[202],"identification":[204],"classification":[206],"pipeline:":[207],"hypothesize":[209],"this":[211],"consequence":[214],"both":[216],"overall":[221],"adequacy":[222],"pipeline":[225],"specificities":[228],"terms":[234],"bias-variance":[236],"tradeoff.":[237]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":12},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":18},{"year":2022,"cited_by_count":2}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}
