{"id":"https://openalex.org/W4391307482","doi":"https://doi.org/10.1109/icspcc59353.2023.10400227","title":"Intelligent Object Detector based on Deep Learning","display_name":"Intelligent Object Detector based on Deep Learning","publication_year":2023,"publication_date":"2023-11-14","ids":{"openalex":"https://openalex.org/W4391307482","doi":"https://doi.org/10.1109/icspcc59353.2023.10400227"},"language":"en","primary_location":{"id":"doi:10.1109/icspcc59353.2023.10400227","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icspcc59353.2023.10400227","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5084977158","display_name":"Huaiyuan Qi","orcid":"https://orcid.org/0000-0003-4616-8207"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huaiyuan Qi","raw_affiliation_strings":["Shaanxi Fenghuo Electronics Company Ltd.,Baoji,China","Shaanxi Fenghuo Electronics Company Ltd., Baoji, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shaanxi Fenghuo Electronics Company Ltd.,Baoji,China","institution_ids":[]},{"raw_affiliation_string":"Shaanxi Fenghuo Electronics Company Ltd., Baoji, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100761671","display_name":"Yuan Zhao","orcid":"https://orcid.org/0000-0003-0468-385X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yuan Zhao","raw_affiliation_strings":["School of Information Engineering, Xi'an Mingde Institute of Technology,Xi'an,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Engineering, Xi'an Mingde Institute of Technology,Xi'an,China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107808023","display_name":"Benben Li","orcid":"https://orcid.org/0009-0007-8980-5970"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Benben Li","raw_affiliation_strings":["School of Electronics and Information, Northwestern Polytechnical University,Xi'an,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronics and Information, Northwestern Polytechnical University,Xi'an,China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010418315","display_name":"Chengkai Tang","orcid":"https://orcid.org/0000-0002-9008-0061"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chengkai Tang","raw_affiliation_strings":["School of Electronics and Information, Northwestern Polytechnical University,Xi'an,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronics and Information, Northwestern Polytechnical University,Xi'an,China","institution_ids":["https://openalex.org/I17145004"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.5409,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.63347256,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14257","display_name":"Advanced Measurement and Detection Methods","score":0.313400000333786,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T14257","display_name":"Advanced Measurement and Detection Methods","score":0.313400000333786,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T14339","display_name":"Image Processing and 3D Reconstruction","score":0.28630000352859497,"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":0.27309998869895935,"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/computer-science","display_name":"Computer science","score":0.7194163203239441},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6005393266677856},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.5880117416381836},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4851146936416626},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.48294705152511597},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4659850001335144},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.45847538113594055},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.2149573266506195},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.08975884318351746}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7194163203239441},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6005393266677856},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.5880117416381836},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4851146936416626},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.48294705152511597},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4659850001335144},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.45847538113594055},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2149573266506195},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.08975884318351746}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icspcc59353.2023.10400227","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icspcc59353.2023.10400227","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W2115178614","https://openalex.org/W2156019871","https://openalex.org/W2194775991","https://openalex.org/W2601113512","https://openalex.org/W2919115771","https://openalex.org/W3167976421","https://openalex.org/W4206029786","https://openalex.org/W4223523758","https://openalex.org/W4286631628","https://openalex.org/W4304998080"],"related_works":["https://openalex.org/W2366906938","https://openalex.org/W4375867731","https://openalex.org/W2349391998","https://openalex.org/W4205655149","https://openalex.org/W2949096641","https://openalex.org/W2970686063","https://openalex.org/W4320729701","https://openalex.org/W3034745255","https://openalex.org/W4254103348","https://openalex.org/W4292830139"],"abstract_inverted_index":{"To":[0],"address":[1],"the":[2,58,63,82,92,97,102],"challenge":[3],"of":[4,104,116],"suboptimal":[5],"performance":[6,55,110],"in":[7,126],"constant":[8],"false":[9,78],"alarm":[10,79],"rate":[11,80],"(CFAR)":[12],"detectors":[13],"due":[14],"to":[15,106,118],"statistical":[16],"model":[17],"mismatch,":[18],"an":[19,35],"intelligent":[20],"detector":[21,33,61,65,85,95],"known":[22],"as":[23],"RepVGG":[24,44,60],"(Re-parameterization":[25],"Visual":[26],"Geometry":[27],"Group)":[28],"has":[29],"been":[30],"introduced.":[31],"This":[32],"leverages":[34],"end-to-end":[36],"deep":[37],"learning":[38],"approach":[39],"and":[40,48,62],"is":[41,111],"structured":[42],"with":[43],"feature":[45],"extraction":[46],"modules":[47],"Rep":[49,83],"VGG":[50,84],"prediction":[51],"output":[52],"modules.":[53],"A":[54],"comparison":[56],"between":[57],"designed":[59],"CFAR":[64],"was":[66],"conducted":[67],"through":[68],"Monte":[69],"Carlo":[70],"experiments.":[71],"The":[72,108],"results":[73],"demonstrate":[74],"that,":[75],"under":[76],"equivalent":[77],"conditions,":[81],"consistently":[86],"achieves":[87],"higher":[88],"detection":[89,127],"probabilities":[90],"than":[91],"CF":[93],"AR":[94],"when":[96],"signal-to-noise":[98,114],"ratio":[99],"falls":[100],"within":[101],"range":[103],"6dB":[105],"15dB.":[107],"optimal":[109],"observed":[112],"at":[113],"ratios":[115],"9dB":[117],"10dB,":[119],"where":[120],"it":[121],"surpasses":[122],"a":[123],"20%":[124],"increase":[125],"probability.":[128]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}