{"id":"https://openalex.org/W4386356802","doi":"https://doi.org/10.12785/ijcds/140165","title":"A Cost-effective Deep Active Learning for Object Detection in Automated Driving Systems","display_name":"A Cost-effective Deep Active Learning for Object Detection in Automated Driving Systems","publication_year":2023,"publication_date":"2023-09-01","ids":{"openalex":"https://openalex.org/W4386356802","doi":"https://doi.org/10.12785/ijcds/140165"},"language":"en","primary_location":{"id":"doi:10.12785/ijcds/140165","doi":"https://doi.org/10.12785/ijcds/140165","is_oa":true,"landing_page_url":"https://doi.org/10.12785/ijcds/140165","pdf_url":"https://journal.uob.edu.bh:443/bitstream/123456789/5169/3/IJCDS140165.pdf","source":{"id":"https://openalex.org/S2765015152","display_name":"International Journal of Computing and Digital Systems","issn_l":"2210-142X","issn":["2210-142X","2535-9886"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","norway-1","poland-20","russia-white-list-3"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Computing and Digital Systems","raw_type":"journal-article"},"volume":null,"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://journal.uob.edu.bh:443/bitstream/123456789/5169/3/IJCDS140165.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5092819976","display_name":"Mohib Khebbache","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210157185","display_name":"University of Eloued","ror":"https://ror.org/05416s909","country_code":"DZ","type":"education","lineage":["https://openalex.org/I4210157185"]}],"countries":["DZ"],"is_corresponding":false,"raw_author_name":"Mohib Khebbache","raw_affiliation_strings":["Department of Computer Science , University Of El Oued , El Oued , Algeria"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science , University Of El Oued , El Oued , Algeria","institution_ids":["https://openalex.org/I4210157185"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048857332","display_name":"Salim Bitam","orcid":"https://orcid.org/0000-0001-5618-4126","observed_orcids":["https://orcid.org/0000-0001-5618-4126"]},"institutions":[{"id":"https://openalex.org/I206961696","display_name":"University of Biskra","ror":"https://ror.org/05fr5y859","country_code":"DZ","type":"education","lineage":["https://openalex.org/I206961696"]}],"countries":["DZ"],"is_corresponding":false,"raw_author_name":"Salim Bitam","raw_affiliation_strings":["Department of Computer Science , University of Biskra , Biskra , Algeria"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science , University of Biskra , Biskra , Algeria","institution_ids":["https://openalex.org/I206961696"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045421775","display_name":"Abdelhamid Mellouk","orcid":"https://orcid.org/0000-0002-6886-7394","observed_orcids":["https://orcid.org/0000-0002-6886-7394"]},"institutions":[{"id":"https://openalex.org/I197681013","display_name":"Universit\u00e9 Paris-Est Cr\u00e9teil","ror":"https://ror.org/05ggc9x40","country_code":"FR","type":"education","lineage":["https://openalex.org/I197681013","https://openalex.org/I2800365227"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Abdelhamid Mellouk","raw_affiliation_strings":["EPISEN , THINCNET , University of Paris-Est Creteil , Vitry sur Seine , France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"EPISEN , THINCNET , University of Paris-Est Creteil , Vitry sur Seine , France","institution_ids":["https://openalex.org/I197681013"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0849,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.31603612,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":93},"biblio":{"volume":"14","issue":"1","first_page":"839","last_page":"854"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9282000064849854,"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":0.9282000064849854,"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":0.03500000014901161,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.025599999353289604,"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/deep-active-learning","display_name":"deep active learning","score":0.9739999771118164},{"id":"https://openalex.org/keywords/traffic-object-detection","display_name":"traffic object detection","score":0.7609999775886536},{"id":"https://openalex.org/keywords/autonomous-driving","display_name":"autonomous driving","score":0.8190000057220459},{"id":"https://openalex.org/keywords/forecast-uncertainty","display_name":"forecast uncertainty","score":0.7149999737739563},{"id":"https://openalex.org/keywords/dynamic-programming","display_name":"dynamic programming","score":0.8339999914169312},{"id":"https://openalex.org/keywords/pedestrian-detection","display_name":"pedestrian detection","score":0.652999997138977},{"id":"https://openalex.org/keywords/yolov3-tiny","display_name":"YOLOv3-tiny","score":0.9210000038146973},{"id":"https://openalex.org/keywords/annotation-cost-reduction","display_name":"annotation cost reduction","score":0.5820000171661377}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6261067390441895},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.551565945148468},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5454980134963989},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5118071436882019},{"id":"https://openalex.org/C77967617","wikidata":"https://www.wikidata.org/wiki/Q4677561","display_name":"Active learning (machine learning)","level":2,"score":0.47636815905570984},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4612096846103668},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.35287684202194214},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3517754375934601},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.3505312502384186},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.13776087760925293}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.12785/ijcds/140165","doi":"https://doi.org/10.12785/ijcds/140165","is_oa":true,"landing_page_url":"https://doi.org/10.12785/ijcds/140165","pdf_url":"https://journal.uob.edu.bh:443/bitstream/123456789/5169/3/IJCDS140165.pdf","source":{"id":"https://openalex.org/S2765015152","display_name":"International Journal of Computing and Digital Systems","issn_l":"2210-142X","issn":["2210-142X","2535-9886"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","norway-1","poland-20","russia-white-list-3"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Computing and Digital Systems","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.12785/ijcds/140165","doi":"https://doi.org/10.12785/ijcds/140165","is_oa":true,"landing_page_url":"https://doi.org/10.12785/ijcds/140165","pdf_url":"https://journal.uob.edu.bh:443/bitstream/123456789/5169/3/IJCDS140165.pdf","source":{"id":"https://openalex.org/S2765015152","display_name":"International Journal of Computing and Digital Systems","issn_l":"2210-142X","issn":["2210-142X","2535-9886"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","norway-1","poland-20","russia-white-list-3"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Computing and Digital Systems","raw_type":"journal-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4386356802.pdf","grobid_xml":"https://content.openalex.org/works/W4386356802.grobid-xml"},"referenced_works_count":56,"referenced_works":["https://openalex.org/W795030991","https://openalex.org/W1650122911","https://openalex.org/W1861492603","https://openalex.org/W2031454541","https://openalex.org/W2086865678","https://openalex.org/W2092135080","https://openalex.org/W2132891752","https://openalex.org/W2161969291","https://openalex.org/W2162741153","https://openalex.org/W2541743403","https://openalex.org/W2774918944","https://openalex.org/W2796347433","https://openalex.org/W2890546378","https://openalex.org/W2893920300","https://openalex.org/W2895451584","https://openalex.org/W2903158431","https://openalex.org/W2911486422","https://openalex.org/W2940510674","https://openalex.org/W2951061410","https://openalex.org/W2953303875","https://openalex.org/W2963296333","https://openalex.org/W2963613834","https://openalex.org/W2964129014","https://openalex.org/W2970624554","https://openalex.org/W2984303785","https://openalex.org/W2998936706","https://openalex.org/W3010762453","https://openalex.org/W3011812021","https://openalex.org/W3015270105","https://openalex.org/W3038844663","https://openalex.org/W3041133507","https://openalex.org/W3046195400","https://openalex.org/W3047572591","https://openalex.org/W3090006835","https://openalex.org/W3111541491","https://openalex.org/W3124576131","https://openalex.org/W3127668069","https://openalex.org/W3177386742","https://openalex.org/W3184557372","https://openalex.org/W3187627504","https://openalex.org/W3188862374","https://openalex.org/W3193305990","https://openalex.org/W3195099242","https://openalex.org/W3205626500","https://openalex.org/W3217617243","https://openalex.org/W4206723194","https://openalex.org/W4210364185","https://openalex.org/W4226176845","https://openalex.org/W4281612374","https://openalex.org/W4291325848","https://openalex.org/W4291366346","https://openalex.org/W4309345163","https://openalex.org/W4312407813","https://openalex.org/W4312595781","https://openalex.org/W4313030842","https://openalex.org/W4403182576"],"related_works":["https://openalex.org/W2991448611","https://openalex.org/W4403385336","https://openalex.org/W3217804345","https://openalex.org/W3174643418","https://openalex.org/W3118457089","https://openalex.org/W4413277863","https://openalex.org/W4293863386","https://openalex.org/W4380446319","https://openalex.org/W2963296333","https://openalex.org/W4391951852"],"abstract_inverted_index":{"In":[0],"Automated":[1],"Driving":[2],"Systems":[3],"(ADS),":[4],"the":[5,11,59,65,70,74,82,85,121,132,142,149,167,196,206],"function":[6],"of":[7,61,67,84,151,205],"detecting":[8],"objects":[9],"on":[10,36,58,166],"road":[12,18,37],"assists":[13],"vehicle":[14],"traffic":[15],"and":[16,44,55,64,90,115,156,209],"improves":[17],"safety.Deep":[19],"Active":[20],"Learning":[21],"(DAL)":[22],"is":[23],"an":[24],"advanced":[25],"training":[26,47,104],"method":[27,41],"suitable":[28,106],"for":[29,107,176],"building":[30],"robust":[31,191],"Convolutional":[32],"Neural":[33],"Network":[34],"(CNN)-based":[35],"object":[38,110],"detection":[39,62,179,192,197],"models.This":[40],"automatically":[42],"selects":[43],"manually":[45],"labels":[46,89],"samples":[48],"that":[49,130,182,194],"are":[50,118],"significantly":[51],"less":[52,199],"noisy,":[53],"non-redundant":[54],"more":[56],"useful.Depending":[57],"complexity":[60],"task":[63],"characteristics":[66],"urban":[68],"scenes,":[69],"batch":[71,76,91,116,127,144,157,211],"selection":[72,123,143],"in":[73,120],"conventional":[75],"mode":[77],"DAL":[78],"can":[79,189],"suffer":[80],"from":[81],"impact":[83],"correlation":[86],"between":[87],"frame":[88],"size":[92,117,145,158,212],"as":[93,95],"well":[94],"variable":[96],"labeling":[97,114,207],"costs.This":[98],"paper":[99],"introduces":[100],"a":[101,126,173],"novel":[102],"cost-effective-based":[103],"approach":[105,162],"CNN-based":[108],"on-road":[109],"detector,":[111],"where":[112],"frames":[113],"considered":[119],"sample":[122,160],"process.We":[124],"propose":[125],"sampling":[128],"strategy":[129],"leverages":[131],"model":[133,193],"prediction":[134],"uncertainty":[135,155],"along":[136],"with":[137],"dynamic":[138],"programming":[139],"to":[140,171,186],"alleviate":[141],"issue.Additionally,":[146],"we":[147],"investigate":[148],"effects":[150],"classification":[152],"uncertainty,":[153],"regression":[154],"during":[159],"selection.Our":[161],"was":[163],"extensively":[164],"validated":[165],"Caltech":[168],"Pedestrian":[169],"dataset":[170],"fine-tune":[172],"pre-trained":[174],"Tiny-YOLOv3":[175],"performing":[177],"pedestrian":[178],"task.Results":[180],"showed":[181],"our":[183],"approach,":[184],"compared":[185],"basic":[187],"methods,":[188],"build":[190],"keeps":[195],"error":[198],"than":[200],"57%,":[201],"saving":[202],"up":[203],"50%":[204],"effort":[208],"alleviating":[210],"dependency.":[213]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2023-09-02T00:00:00"}