{"id":"https://openalex.org/W4205524137","doi":"https://doi.org/10.3390/e24010077","title":"Domain-Specific On-Device Object Detection Method","display_name":"Domain-Specific On-Device Object Detection Method","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4205524137","doi":"https://doi.org/10.3390/e24010077","pmid":"https://pubmed.ncbi.nlm.nih.gov/35052102"},"language":"en","primary_location":{"id":"doi:10.3390/e24010077","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e24010077","pdf_url":"https://www.mdpi.com/1099-4300/24/1/77/pdf?version=1641295221","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"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":"Entropy","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/1099-4300/24/1/77/pdf?version=1641295221","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5070062999","display_name":"Seongju Kang","orcid":"https://orcid.org/0000-0001-8306-2028"},"institutions":[{"id":"https://openalex.org/I161024014","display_name":"Kwangwoon University","ror":"https://ror.org/02e9zc863","country_code":"KR","type":"education","lineage":["https://openalex.org/I161024014"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Seongju Kang","raw_affiliation_strings":["Department of Electronics and Communications Engineering, Kwangwoon University, Seoul 01897, Korea"],"raw_orcid":"https://orcid.org/0000-0001-8306-2028","affiliations":[{"raw_affiliation_string":"Department of Electronics and Communications Engineering, Kwangwoon University, Seoul 01897, Korea","institution_ids":["https://openalex.org/I161024014"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047117728","display_name":"Jaegi Hwang","orcid":null},"institutions":[{"id":"https://openalex.org/I161024014","display_name":"Kwangwoon University","ror":"https://ror.org/02e9zc863","country_code":"KR","type":"education","lineage":["https://openalex.org/I161024014"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jaegi Hwang","raw_affiliation_strings":["Department of Electronics and Communications Engineering, Kwangwoon University, Seoul 01897, Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronics and Communications Engineering, Kwangwoon University, Seoul 01897, Korea","institution_ids":["https://openalex.org/I161024014"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5030905971","display_name":"Kwangsue Chung","orcid":"https://orcid.org/0000-0002-0283-0900"},"institutions":[{"id":"https://openalex.org/I161024014","display_name":"Kwangwoon University","ror":"https://ror.org/02e9zc863","country_code":"KR","type":"education","lineage":["https://openalex.org/I161024014"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Kwangsue Chung","raw_affiliation_strings":["Department of Electronics and Communications Engineering, Kwangwoon University, Seoul 01897, Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronics and Communications Engineering, Kwangwoon University, Seoul 01897, Korea","institution_ids":["https://openalex.org/I161024014"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5030905971"],"corresponding_institution_ids":["https://openalex.org/I161024014"],"apc_list":{"value":2000,"currency":"CHF","value_usd":2165},"apc_paid":{"value":2000,"currency":"CHF","value_usd":2165},"fwci":0.2032,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.44616142,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"24","issue":"1","first_page":"77","last_page":"77"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998999834060669,"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":0.9998999834060669,"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/T11605","display_name":"Visual Attention and Saliency Detection","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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9962000250816345,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing 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/computer-science","display_name":"Computer science","score":0.7992099523544312},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.7090844511985779},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.6685453653335571},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.6467953324317932},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.6244037747383118},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5497518181800842},{"id":"https://openalex.org/keywords/mobile-device","display_name":"Mobile device","score":0.5225962400436401},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.5217279195785522},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4865080714225769},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.46437278389930725},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.41035494208335876},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.18108662962913513},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11095064878463745}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7992099523544312},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.7090844511985779},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.6685453653335571},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.6467953324317932},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.6244037747383118},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5497518181800842},{"id":"https://openalex.org/C186967261","wikidata":"https://www.wikidata.org/wiki/Q5082128","display_name":"Mobile device","level":2,"score":0.5225962400436401},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.5217279195785522},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4865080714225769},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.46437278389930725},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.41035494208335876},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.18108662962913513},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11095064878463745},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.3390/e24010077","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e24010077","pdf_url":"https://www.mdpi.com/1099-4300/24/1/77/pdf?version=1641295221","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"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":"Entropy","raw_type":"journal-article"},{"id":"pmid:35052102","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35052102","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":"Entropy (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:doaj.org/article:881e3ab988004a83be56c261639fd495","is_oa":true,"landing_page_url":"https://doaj.org/article/881e3ab988004a83be56c261639fd495","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":"Entropy, Vol 24, Iss 1, p 77 (2022)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1099-4300/24/1/77/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/e24010077","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":"Entropy; Volume 24; Issue 1; Pages: 77","raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:8775011","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8775011","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":"Entropy (Basel)","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/e24010077","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e24010077","pdf_url":"https://www.mdpi.com/1099-4300/24/1/77/pdf?version=1641295221","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"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":"Entropy","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1363189855","display_name":null,"funder_award_id":"2020-0-00959","funder_id":"https://openalex.org/F4320328359","funder_display_name":"Ministry of Science and ICT, South Korea"},{"id":"https://openalex.org/G642915127","display_name":null,"funder_award_id":"2020-0-00959","funder_id":"https://openalex.org/F4320335489","funder_display_name":"Institute for Information and Communications Technology Promotion"}],"funders":[{"id":"https://openalex.org/F4320328359","display_name":"Ministry of Science and ICT, South Korea","ror":"https://ror.org/01wpjm123"},{"id":"https://openalex.org/F4320335489","display_name":"Institute for Information and Communications Technology Promotion","ror":"https://ror.org/01g0hqq23"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4205524137.pdf","grobid_xml":"https://content.openalex.org/works/W4205524137.grobid-xml"},"referenced_works_count":21,"referenced_works":["https://openalex.org/W46659105","https://openalex.org/W1607307044","https://openalex.org/W2031489346","https://openalex.org/W2097117768","https://openalex.org/W2194775991","https://openalex.org/W2233116163","https://openalex.org/W2294370754","https://openalex.org/W2300242332","https://openalex.org/W2900757645","https://openalex.org/W2927435109","https://openalex.org/W2942267387","https://openalex.org/W2962804345","https://openalex.org/W2963163009","https://openalex.org/W2963446712","https://openalex.org/W2980856918","https://openalex.org/W2998153539","https://openalex.org/W3000322757","https://openalex.org/W3004633656","https://openalex.org/W3096609285","https://openalex.org/W3118608800","https://openalex.org/W3176049234"],"related_works":["https://openalex.org/W3034529322","https://openalex.org/W2046435967","https://openalex.org/W2113597336","https://openalex.org/W2155505549","https://openalex.org/W4231775656","https://openalex.org/W2115913271","https://openalex.org/W2357479218","https://openalex.org/W1819546284","https://openalex.org/W2018648706","https://openalex.org/W2114232034"],"abstract_inverted_index":{"Object":[0],"detection":[1,44,116],"is":[2,30,130,134],"a":[3,64,102],"significant":[4],"activity":[5],"in":[6,69],"computer":[7],"vision,":[8],"and":[9,86,136,143,158,166,179,189],"various":[10,108],"approaches":[11],"have":[12],"been":[13],"proposed":[14,51,127],"to":[15,32,35,111],"detect":[16],"varied":[17],"objects":[18,62],"using":[19,46],"deep":[20],"neural":[21],"networks":[22],"(DNNs).":[23],"However,":[24],"because":[25],"DNNs":[26],"are":[27,84],"computation-intensive,":[28],"it":[29],"difficult":[31],"apply":[33],"them":[34],"resource-constrained":[36],"devices.":[37],"Here,":[38],"we":[39,53,106],"propose":[40],"an":[41],"on-device":[42],"object":[43,55,98],"method":[45],"domain-specific":[47,82],"models.":[48,194],"In":[49],"the":[50,74,78,81,89,97,113,123,126,150,173],"method,":[52],"define":[54],"of":[56,67,80,91,125,141,163],"interest":[57],"(OOI)":[58],"groups":[59],"that":[60,122,172],"contain":[61],"with":[63,73],"high":[65],"frequency":[66],"appearance":[68],"specific":[70],"domains.":[71],"Compared":[72],"existing":[75],"DNN":[76],"model,":[77],"layers":[79],"models":[83],"shallower":[85],"narrower,":[87],"reducing":[88],"number":[90],"trainable":[92],"parameters;":[93],"thus,":[94],"speeding":[95],"up":[96],"detection.":[99],"To":[100],"ensure":[101],"lightweight":[103,115,128,174],"network":[104,109],"design,":[105],"combine":[107],"structures":[110],"obtain":[112],"best-performing":[114],"model.":[117],"The":[118,146,169],"experimental":[119],"results":[120,170],"reveal":[121],"size":[124],"model":[129,175],"21.7":[131],"MB,":[132],"which":[133],"91.35%":[135],"36.98%":[137],"smaller":[138],"than":[139,161,192],"those":[140,162],"YOLOv3-SPP":[142],"Tiny-YOLO,":[144],"respectively.":[145,168],"f-measure":[147],"achieved":[148,176],"on":[149,182],"MS":[151],"COCO":[152],"2017":[153],"dataset":[154],"were":[155],"18.3%,":[156],"11.9%":[157],"20.3%":[159],"higher":[160,177],"YOLOv3-SPP,":[164],"Tiny-YOLO":[165],"YOLO-Nano,":[167],"demonstrated":[171],"efficiency":[178],"better":[180],"performance":[181],"non-GPU":[183],"devices,":[184],"such":[185],"as":[186],"mobile":[187],"devices":[188],"embedded":[190],"boards,":[191],"conventional":[193]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}
