{"id":"https://openalex.org/W4214777592","doi":"https://doi.org/10.1145/3488933.3488956","title":"Research on Crowd Counting Algorithm Based on Multi-scale Adaptive Network","display_name":"Research on Crowd Counting Algorithm Based on Multi-scale Adaptive Network","publication_year":2021,"publication_date":"2021-09-24","ids":{"openalex":"https://openalex.org/W4214777592","doi":"https://doi.org/10.1145/3488933.3488956"},"language":"en","primary_location":{"id":"doi:10.1145/3488933.3488956","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3488933.3488956","pdf_url":null,"source":{"id":"https://openalex.org/S4363608564","display_name":"2021 4th International Conference on Artificial Intelligence and Pattern Recognition","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":"2021 4th International Conference on Artificial Intelligence and Pattern Recognition","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/A5013798584","display_name":"Feng Min","orcid":"https://orcid.org/0000-0002-6846-8916"},"institutions":[{"id":"https://openalex.org/I91125648","display_name":"Wuhan Institute of Technology","ror":"https://ror.org/04jcykh16","country_code":"CN","type":"education","lineage":["https://openalex.org/I91125648"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Feng Min","raw_affiliation_strings":["Wuhan Institute of Technology, China"],"affiliations":[{"raw_affiliation_string":"Wuhan Institute of Technology, China","institution_ids":["https://openalex.org/I91125648"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101026178","display_name":"Tianzi Gu","orcid":"https://orcid.org/0000-0002-8608-9100"},"institutions":[{"id":"https://openalex.org/I91125648","display_name":"Wuhan Institute of Technology","ror":"https://ror.org/04jcykh16","country_code":"CN","type":"education","lineage":["https://openalex.org/I91125648"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianzi Gu","raw_affiliation_strings":["Wuhan Institute of Technology, China"],"affiliations":[{"raw_affiliation_string":"Wuhan Institute of Technology, China","institution_ids":["https://openalex.org/I91125648"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5013798584"],"corresponding_institution_ids":["https://openalex.org/I91125648"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.22249424,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"303","last_page":"308"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9998999834060669,"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/T10331","display_name":"Video Surveillance and Tracking Methods","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/T12597","display_name":"Fire Detection and Safety Systems","score":0.9789000153541565,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"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/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9753000140190125,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.7565072774887085},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.7314667701721191},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6940534114837646},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.6003618240356445},{"id":"https://openalex.org/keywords/pyramid","display_name":"Pyramid (geometry)","score":0.5915575623512268},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5808712840080261},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5587319135665894},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.5573468208312988},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5342259407043457},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4853709936141968},{"id":"https://openalex.org/keywords/variable","display_name":"Variable (mathematics)","score":0.41252601146698},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3918338119983673},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.38912299275398254},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.2788006663322449},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2361687421798706}],"concepts":[{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.7565072774887085},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7314667701721191},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6940534114837646},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.6003618240356445},{"id":"https://openalex.org/C142575187","wikidata":"https://www.wikidata.org/wiki/Q3358290","display_name":"Pyramid (geometry)","level":2,"score":0.5915575623512268},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5808712840080261},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5587319135665894},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.5573468208312988},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5342259407043457},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4853709936141968},{"id":"https://openalex.org/C182365436","wikidata":"https://www.wikidata.org/wiki/Q50701","display_name":"Variable (mathematics)","level":2,"score":0.41252601146698},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3918338119983673},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.38912299275398254},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2788006663322449},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2361687421798706},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"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/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3488933.3488956","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3488933.3488956","pdf_url":null,"source":{"id":"https://openalex.org/S4363608564","display_name":"2021 4th International Conference on Artificial Intelligence and Pattern Recognition","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":"2021 4th International Conference on Artificial Intelligence and Pattern Recognition","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1910776219","https://openalex.org/W1978232622","https://openalex.org/W1992825118","https://openalex.org/W2072232009","https://openalex.org/W2097324787","https://openalex.org/W2109255472","https://openalex.org/W2125337786","https://openalex.org/W2151666244","https://openalex.org/W2155916750","https://openalex.org/W2463631526","https://openalex.org/W2541389513","https://openalex.org/W2741077351","https://openalex.org/W2752782242","https://openalex.org/W2794341924","https://openalex.org/W2798490576","https://openalex.org/W2964209782","https://openalex.org/W6673666323","https://openalex.org/W6729211573"],"related_works":["https://openalex.org/W2022849497","https://openalex.org/W2810679507","https://openalex.org/W3081299480","https://openalex.org/W2407190427","https://openalex.org/W2907584218","https://openalex.org/W2919210741","https://openalex.org/W3002446410","https://openalex.org/W4390224712","https://openalex.org/W4322096758","https://openalex.org/W2964954556"],"abstract_inverted_index":{"The":[0,44,113],"variable":[1],"spatial":[2,60],"scale":[3],"and":[4,58,85,98,120,149,160,178,197],"crowd":[5,8,16,30],"distribution":[6],"in":[7,19,41,142,157,191],"images":[9,72],"are":[10,52,79,88,101],"the":[11,26,49,59,68,96,105,117,127,131,134,138,152,155,161,169,172,179,188],"main":[12],"challenges":[13],"faced":[14],"by":[15,90,147,166,176,183],"counting":[17,31],"problems":[18],"recent":[20],"years.":[21],"In":[22],"order":[23],"to":[24,54,66,71,103,110],"solve":[25],"above":[27],"problems,":[28],"a":[29,35],"method":[32,189],"based":[33],"on":[34,116],"multi-scale":[36,77],"adaptive":[37],"network":[38,51,69],"is":[39,64,145,154,164,174,181],"proposed":[40,190],"this":[42,143,192],"paper.":[43],"first":[45],"10":[46],"layers":[47],"of":[48,73,107,133,137],"VGG-16":[50],"used":[53],"extract":[55],"basic":[56,93],"features,":[57],"pyramid":[61],"pooling":[62],"layer":[63],"introduced":[65],"make":[67],"adapt":[70],"any":[74],"size.":[75],"Then,":[76],"features":[78,87],"extracted":[80],"through":[81],"hybrid":[82],"dilated":[83],"convolution,":[84],"contrast":[86,111],"obtained":[89],"comparing":[91],"with":[92,126],"features.":[94,112],"Finally,":[95],"weight":[97],"density":[99],"map":[100],"calculated":[102],"obtain":[104],"number":[106],"people":[108],"according":[109],"experimental":[114],"results":[115],"Shanghai":[118,139],"Tech":[119,140],"UCF_CC_50":[121,170],"datasets":[122],"show":[123],"that,":[124],"compared":[125],"previous":[128],"best":[129],"method,":[130],"MAE":[132,173],"two":[135],"parts":[136],"dataset":[141],"paper":[144,193],"reduced":[146,165,175,182],"1.1":[148],"0.1,":[150],"respectively,":[151],"MSE":[153,180],"same":[156],"part":[158,162],"A,":[159],"B":[163],"0.2.":[167],"On":[168],"dataset,":[171],"10.9,":[177],"61.4.":[184],"It":[185],"shows":[186],"that":[187],"has":[194],"better":[195],"accuracy":[196],"robustness.":[198]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
