{"id":"https://openalex.org/W4411446232","doi":"https://doi.org/10.1109/access.2025.3581428","title":"Ghost Module-Enhanced MTCNN: A Lightweight Cascade Framework for High-Accuracy Face Detection in Edge-Deployable Scenarios","display_name":"Ghost Module-Enhanced MTCNN: A Lightweight Cascade Framework for High-Accuracy Face Detection in Edge-Deployable Scenarios","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4411446232","doi":"https://doi.org/10.1109/access.2025.3581428"},"language":"en","primary_location":{"id":"doi:10.1109/access.2025.3581428","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3581428","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2025.3581428","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Chen Wang","orcid":"https://orcid.org/0009-0000-1092-6147"},"institutions":[{"id":"https://openalex.org/I133270356","display_name":"Tianjin University of Technology and Education","ror":"https://ror.org/035gwtk09","country_code":"CN","type":"education","lineage":["https://openalex.org/I133270356"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chen Wang","raw_affiliation_strings":["Electronic Engineering Department, Tianjin University of Technology and Education, Tianjin, China","Electronic Engineering Department, Tianjin University of Technology, Education, Tianjin, China"],"raw_orcid":"https://orcid.org/0009-0000-1092-6147","affiliations":[{"raw_affiliation_string":"Electronic Engineering Department, Tianjin University of Technology and Education, Tianjin, China","institution_ids":["https://openalex.org/I133270356"]},{"raw_affiliation_string":"Electronic Engineering Department, Tianjin University of Technology, Education, Tianjin, China","institution_ids":["https://openalex.org/I133270356"]}]},{"author_position":"last","author":{"id":null,"display_name":"Fen Liu","orcid":"https://orcid.org/0009-0009-5658-1637"},"institutions":[{"id":"https://openalex.org/I133270356","display_name":"Tianjin University of Technology and Education","ror":"https://ror.org/035gwtk09","country_code":"CN","type":"education","lineage":["https://openalex.org/I133270356"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fen Liu","raw_affiliation_strings":["Electronic Engineering Department, Tianjin University of Technology and Education, Tianjin, China","Electronic Engineering Department, Tianjin University of Technology, Education, Tianjin, China"],"raw_orcid":"https://orcid.org/0009-0009-5658-1637","affiliations":[{"raw_affiliation_string":"Electronic Engineering Department, Tianjin University of Technology and Education, Tianjin, China","institution_ids":["https://openalex.org/I133270356"]},{"raw_affiliation_string":"Electronic Engineering Department, Tianjin University of Technology, Education, Tianjin, China","institution_ids":["https://openalex.org/I133270356"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I133270356"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":6.7251,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.95848257,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":"13","issue":null,"first_page":"107694","last_page":"107709"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9890999794006348,"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"}},"topics":[{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9890999794006348,"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"}},{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.9682999849319458,"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/T13382","display_name":"Robotics and Automated Systems","score":0.9667999744415283,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/cascade","display_name":"Cascade","score":0.7755932211875916},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.732253909111023},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.6455254554748535},{"id":"https://openalex.org/keywords/face-detection","display_name":"Face detection","score":0.5752967596054077},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.5678200721740723},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48803654313087463},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4082528054714203},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.3864081799983978},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.3748170733451843},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.25026196241378784},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1336805820465088}],"concepts":[{"id":"https://openalex.org/C34146451","wikidata":"https://www.wikidata.org/wiki/Q5048094","display_name":"Cascade","level":2,"score":0.7755932211875916},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.732253909111023},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.6455254554748535},{"id":"https://openalex.org/C4641261","wikidata":"https://www.wikidata.org/wiki/Q11681085","display_name":"Face detection","level":4,"score":0.5752967596054077},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.5678200721740723},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48803654313087463},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4082528054714203},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.3864081799983978},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.3748170733451843},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.25026196241378784},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1336805820465088},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C42360764","wikidata":"https://www.wikidata.org/wiki/Q83588","display_name":"Chemical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2025.3581428","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3581428","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:015718c66c224b9594db797498a7d589","is_oa":true,"landing_page_url":"https://doaj.org/article/015718c66c224b9594db797498a7d589","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":"IEEE Access, Vol 13, Pp 107694-107709 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2025.3581428","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3581428","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1849277567","https://openalex.org/W1934410531","https://openalex.org/W2041497292","https://openalex.org/W2097117768","https://openalex.org/W2102605133","https://openalex.org/W2194775991","https://openalex.org/W2209882149","https://openalex.org/W2217896605","https://openalex.org/W2341528187","https://openalex.org/W2570343428","https://openalex.org/W2618530766","https://openalex.org/W2911651131","https://openalex.org/W2963037989","https://openalex.org/W2963351448","https://openalex.org/W2963566548","https://openalex.org/W2982215948","https://openalex.org/W3035414587","https://openalex.org/W3097096317","https://openalex.org/W4380632960","https://openalex.org/W4392981161","https://openalex.org/W6620707391","https://openalex.org/W6637373629","https://openalex.org/W6750227808","https://openalex.org/W6756579179","https://openalex.org/W6849520326"],"related_works":["https://openalex.org/W1967587236","https://openalex.org/W2384651879","https://openalex.org/W2336272890","https://openalex.org/W2151699605","https://openalex.org/W4308999381","https://openalex.org/W4312238398","https://openalex.org/W3211418293","https://openalex.org/W4308999963","https://openalex.org/W2133653344","https://openalex.org/W4312081214"],"abstract_inverted_index":{"Face":[0],"detection":[1,183],"in":[2,34,67,107,146,166,174],"complex":[3,175],"environments":[4,173],"remains":[5],"challenging":[6],"due":[7],"to":[8,110,114,161],"trade-offs":[9],"between":[10],"accuracy":[11,95,126],"and":[12,82,88,99,130,152,171,182],"computational":[13,56],"efficiency,":[14],"particularly":[15],"for":[16,190],"edge":[17,193],"devices":[18],"with":[19,102],"limited":[20],"resources.":[21],"GhostNet-MTCNN":[22],"is":[23],"proposed.":[24],"In":[25,112],"this":[26],"approach,":[27],"the":[28,35,50,61,75,85,92,116,119,158],"computationally":[29],"intensive":[30],"standard":[31],"convolution":[32,147],"layers":[33],"Multi-task":[36],"Cascaded":[37],"Convolutional":[38],"Neural":[39],"Network":[40],"(MTCNN)":[41],"backbone":[42],"are":[43],"replaced":[44],"by":[45,96,122,127],"Ghost":[46],"bottleneck":[47],"modules":[48],"from":[49],"GhostNet":[51],"network,":[52],"which":[53],"offer":[54],"lower":[55],"requirements.":[57],"This":[58,155],"modification":[59],"reconstructs":[60],"network\u2019s":[62],"feature":[63],"extraction":[64],"capabilities,":[65],"resulting":[66],"a":[68,104,143,187],"new":[69],"model.":[70],"Experimental":[71],"results":[72],"demonstrate":[73],"that":[74],"proposed":[76],"method":[77,93],"effectively":[78,178],"balances":[79],"model":[80,117],"parameters":[81,108],"accuracy.":[83],"On":[84],"Easy,":[86],"Medium,":[87],"Hard":[89],"validation":[90],"sets,":[91],"improves":[94],"5.6%,":[97],"6.6%,":[98],"7.8%,":[100],"respectively,":[101],"only":[103],"0.62M":[105],"increase":[106],"compared":[109],"MTCNN.":[111],"comparison":[113],"MobileNetV3-MTCNN,":[115],"reduces":[118],"parameter":[120,180],"count":[121,181],"1.27M":[123],"while":[124,177],"improving":[125],"1.6%,":[128],"0.8%,":[129],"0.5%,":[131],"respectively.":[132],"Hardware":[133],"deployment":[134,191],"on":[135,192],"FPGA":[136],"further":[137],"validates":[138],"its":[139],"practical":[140],"efficacy,":[141],"achieving":[142],"400\u00d7":[144],"acceleration":[145],"operations":[148],"through":[149],"optimized":[150],"parallelization":[151],"memory":[153],"caching.":[154],"study":[156],"enhances":[157],"model\u2019s":[159],"ability":[160],"detect":[162],"small-size,":[163],"multi-angle":[164],"faces":[165],"low":[167],"light,":[168],"partially":[169],"occluded,":[170],"noisy":[172],"scenarios,":[176],"balancing":[179],"accuracy,":[184],"making":[185],"it":[186],"superior":[188],"choice":[189],"devices.":[194]},"counts_by_year":[{"year":2026,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
