{"id":"https://openalex.org/W4414250427","doi":"https://doi.org/10.1007/978-3-032-04968-1_3","title":"Multi-task Pedestrian Attribute Classification Using ConvNeXt with\u00a0Advanced Data Augmentation","display_name":"Multi-task Pedestrian Attribute Classification Using ConvNeXt with\u00a0Advanced Data Augmentation","publication_year":2025,"publication_date":"2025-09-16","ids":{"openalex":"https://openalex.org/W4414250427","doi":"https://doi.org/10.1007/978-3-032-04968-1_3"},"language":"en","primary_location":{"id":"doi:10.1007/978-3-032-04968-1_3","is_oa":false,"landing_page_url":"https://doi.org/10.1007/978-3-032-04968-1_3","pdf_url":null,"source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"},"type":"book-chapter","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/A5034751193","display_name":"Magzhan Kairanbay","orcid":"https://orcid.org/0000-0002-8741-434X"},"institutions":[{"id":"https://openalex.org/I4210134662","display_name":"Bahrain Center for Strategic International and Energy Studies","ror":"https://ror.org/03ht6cj06","country_code":"BH","type":"other","lineage":["https://openalex.org/I4210134662"]}],"countries":["BH"],"is_corresponding":true,"raw_author_name":"Magzhan Kairanbay","raw_affiliation_strings":["Array Innovation, Al Baraka Tower A, Building 372, Road 4611, Block 346, Manama, Bahrain"],"raw_orcid":"https://orcid.org/0000-0002-8741-434X","affiliations":[{"raw_affiliation_string":"Array Innovation, Al Baraka Tower A, Building 372, Road 4611, Block 346, Manama, Bahrain","institution_ids":["https://openalex.org/I4210134662"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5030061643","display_name":"Ali N. Salman","orcid":"https://orcid.org/0000-0003-1395-0382"},"institutions":[{"id":"https://openalex.org/I4210134662","display_name":"Bahrain Center for Strategic International and Energy Studies","ror":"https://ror.org/03ht6cj06","country_code":"BH","type":"other","lineage":["https://openalex.org/I4210134662"]}],"countries":["BH"],"is_corresponding":false,"raw_author_name":"Ali Salman","raw_affiliation_strings":["Array Innovation, Al Baraka Tower A, Building 372, Road 4611, Block 346, Manama, Bahrain"],"raw_orcid":"https://orcid.org/0000-0003-1395-0382","affiliations":[{"raw_affiliation_string":"Array Innovation, Al Baraka Tower A, Building 372, Road 4611, Block 346, Manama, Bahrain","institution_ids":["https://openalex.org/I4210134662"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5034751193"],"corresponding_institution_ids":["https://openalex.org/I4210134662"],"apc_list":{"value":5000,"currency":"EUR","value_usd":5392},"apc_paid":null,"fwci":6.6736,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.97333966,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"27","last_page":"38"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9961000084877014,"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":0.9961000084877014,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9894000291824341,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9871000051498413,"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/pedestrian","display_name":"Pedestrian","score":0.8407999873161316},{"id":"https://openalex.org/keywords/pedestrian-detection","display_name":"Pedestrian detection","score":0.7149999737739563},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.6373000144958496},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.49790000915527344},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.46129998564720154},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.44749999046325684}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8948000073432922},{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.8407999873161316},{"id":"https://openalex.org/C2780156472","wikidata":"https://www.wikidata.org/wiki/Q2355550","display_name":"Pedestrian detection","level":3,"score":0.7149999737739563},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.680899977684021},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.6373000144958496},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5042999982833862},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.49790000915527344},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.46129998564720154},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.44749999046325684},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.43849998712539673},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3346000015735626},{"id":"https://openalex.org/C530175646","wikidata":"https://www.wikidata.org/wiki/Q11460","display_name":"Clothing","level":2,"score":0.2838999927043915},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.26930001378059387},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.2685000002384186},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.259799987077713}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/978-3-032-04968-1_3","is_oa":false,"landing_page_url":"https://doi.org/10.1007/978-3-032-04968-1_3","pdf_url":null,"source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W1967988963","https://openalex.org/W2410968923","https://openalex.org/W2913340405","https://openalex.org/W2949736877","https://openalex.org/W2963677766","https://openalex.org/W2992308087","https://openalex.org/W4312443924","https://openalex.org/W4386870064","https://openalex.org/W4386870075"],"related_works":[],"abstract_inverted_index":null,"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2026-05-13T08:25:38.343686","created_date":"2025-10-10T00:00:00"}