{"id":"https://openalex.org/W4307335276","doi":"https://doi.org/10.1145/3558819.3565142","title":"A dual-channel SSD pedestrian detection algorithm based on feature fusion","display_name":"A dual-channel SSD pedestrian detection algorithm based on feature fusion","publication_year":2022,"publication_date":"2022-09-23","ids":{"openalex":"https://openalex.org/W4307335276","doi":"https://doi.org/10.1145/3558819.3565142"},"language":"en","primary_location":{"id":"doi:10.1145/3558819.3565142","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3558819.3565142","pdf_url":null,"source":{"id":"https://openalex.org/S4363608855","display_name":"Proceedings of the 7th International Conference on Cyber Security and Information Engineering","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 7th International Conference on Cyber Security and Information Engineering","raw_type":"proceedings-article"},"type":"article","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/A5018911020","display_name":"Jiangkun Lu","orcid":"https://orcid.org/0000-0002-7896-2790"},"institutions":[{"id":"https://openalex.org/I168337820","display_name":"Chongqing University of Science and Technology","ror":"https://ror.org/03n3v6d52","country_code":"CN","type":"education","lineage":["https://openalex.org/I168337820"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jiangkun Lu","raw_affiliation_strings":["Chongqing College of Humanities, Science & Technology, China"],"affiliations":[{"raw_affiliation_string":"Chongqing College of Humanities, Science & Technology, China","institution_ids":["https://openalex.org/I168337820"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5008473103","display_name":"Hongyang Chen","orcid":"https://orcid.org/0000-0002-7626-0162"},"institutions":[{"id":"https://openalex.org/I168337820","display_name":"Chongqing University of Science and Technology","ror":"https://ror.org/03n3v6d52","country_code":"CN","type":"education","lineage":["https://openalex.org/I168337820"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongyang Chen","raw_affiliation_strings":["Chongqing College of Humanities, Science & Technology, China"],"affiliations":[{"raw_affiliation_string":"Chongqing College of Humanities, Science & Technology, China","institution_ids":["https://openalex.org/I168337820"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5018911020"],"corresponding_institution_ids":["https://openalex.org/I168337820"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.1004563,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"550","last_page":"553"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9970999956130981,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9970999956130981,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9930999875068665,"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/T13282","display_name":"Automated Road and Building Extraction","score":0.9728999733924866,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean 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/fuse","display_name":"Fuse (electrical)","score":0.8276057839393616},{"id":"https://openalex.org/keywords/pedestrian-detection","display_name":"Pedestrian detection","score":0.7639723420143127},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6968420743942261},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.657249927520752},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.6361270546913147},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5933584570884705},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.586448609828949},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.48357221484184265},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.46642833948135376},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.4523235261440277},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4518139958381653},{"id":"https://openalex.org/keywords/image-fusion","display_name":"Image fusion","score":0.44604435563087463},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.4319503605365753},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3954232335090637},{"id":"https://openalex.org/keywords/pedestrian","display_name":"Pedestrian","score":0.3790629506111145},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.12120792269706726},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.07734978199005127}],"concepts":[{"id":"https://openalex.org/C141353440","wikidata":"https://www.wikidata.org/wiki/Q182221","display_name":"Fuse (electrical)","level":2,"score":0.8276057839393616},{"id":"https://openalex.org/C2780156472","wikidata":"https://www.wikidata.org/wiki/Q2355550","display_name":"Pedestrian detection","level":3,"score":0.7639723420143127},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6968420743942261},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.657249927520752},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.6361270546913147},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5933584570884705},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.586448609828949},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.48357221484184265},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.46642833948135376},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.4523235261440277},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4518139958381653},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.44604435563087463},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.4319503605365753},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3954232335090637},{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.3790629506111145},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.12120792269706726},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.07734978199005127},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3558819.3565142","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3558819.3565142","pdf_url":null,"source":{"id":"https://openalex.org/S4363608855","display_name":"Proceedings of the 7th International Conference on Cyber Security and Information Engineering","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 7th International Conference on Cyber Security and Information Engineering","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.550000011920929,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":4,"referenced_works":["https://openalex.org/W2891336752","https://openalex.org/W3030109290","https://openalex.org/W4240085721","https://openalex.org/W4253563357"],"related_works":["https://openalex.org/W2972620127","https://openalex.org/W2981141433","https://openalex.org/W2802018156","https://openalex.org/W2095903272","https://openalex.org/W2391745328","https://openalex.org/W4214649316","https://openalex.org/W2554790198","https://openalex.org/W2101531944","https://openalex.org/W4313315626","https://openalex.org/W2922437833"],"abstract_inverted_index":{"In":[0,50],"order":[1],"to":[2,84,107],"solve":[3],"the":[4,13,19,51,56,62,69,75,86,93,97,102,110,121,127,132,145,150,163],"phenomenon":[5],"of":[6,21,113,144,152,165],"false":[7],"detection":[8,11,35,44,133,154,164],"and":[9,23,47,58,71,104,131,159,161],"missed":[10,153],"in":[12,25,61,74,79,96],"pedestrian":[14,34,43,114],"counting":[15],"algorithm":[16,36,123],"caused":[17,155],"by":[18,156],"change":[20],"occlusion":[22,48],"illumination":[24,46,157],"crowded":[26],"scenes,":[27],"this":[28],"paper":[29],"proposes":[30],"a":[31],"dual-channel":[32,52,88],"SSD":[33,53,89,146],"based":[37],"on":[38,126],"feature":[39,111],"fusion,":[40],"which":[41,138,148],"improves":[42,149],"under":[45],"conditions.":[49],"network":[54,90,98],"structure,":[55],"Conv4_3":[57,70],"FC7":[59,72],"layers":[60,73,106],"color":[63],"image":[64,77],"channel":[65,78],"are":[66],"fused":[67,100],"with":[68,101],"depth":[76],"Concat":[80],"or":[81],"Eltwise":[82],"ways":[83],"obtain":[85],"optimal":[87],"model.":[91],"Then,":[92],"Conv4_3_Fuse":[94],"layer":[95],"is":[99,124,136,139],"Conv10_2_Fuse":[103],"Conv11_2_Fuse":[105],"fully":[108],"learn":[109],"information":[112],"heads.":[115],"The":[116],"experimental":[117],"results":[118],"show":[119],"that":[120,143],"improved":[122],"tested":[125],"TVHeads":[128],"data":[129],"set,":[130],"accuracy":[134],"obtained":[135],"95.4%,":[137],"13.16%":[140],"higher":[141],"than":[142],"algorithm,":[147],"problem":[151],"changes":[158],"occlusion,":[160],"enhances":[162],"pedestrians":[166],"head":[167],"recognition.":[168]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}