{"id":"https://openalex.org/W2883309252","doi":"https://doi.org/10.2352/issn.2470-1173.2018.15.coimg-201","title":"Deep Gang Graffiti Component Analysis","display_name":"Deep Gang Graffiti Component Analysis","publication_year":2018,"publication_date":"2018-01-28","ids":{"openalex":"https://openalex.org/W2883309252","doi":"https://doi.org/10.2352/issn.2470-1173.2018.15.coimg-201","mag":"2883309252"},"language":"en","primary_location":{"id":"doi:10.2352/issn.2470-1173.2018.15.coimg-201","is_oa":false,"landing_page_url":"https://doi.org/10.2352/issn.2470-1173.2018.15.coimg-201","pdf_url":null,"source":{"id":"https://openalex.org/S4210227276","display_name":"Electronic Imaging","issn_l":"2470-1173","issn":["2470-1173"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Electronic Imaging","raw_type":"journal-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/A5100317883","display_name":"He Li","orcid":"https://orcid.org/0000-0002-7243-6474"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"He Li","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014398877","display_name":"Joonsoo Kim","orcid":"https://orcid.org/0000-0002-6470-0773"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Joonsoo Kim","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5089688702","display_name":"Edward J. Delp","orcid":"https://orcid.org/0000-0002-2909-7323"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Edward J. Delp","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.3219,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.84726526,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"30","issue":"15","first_page":"201","last_page":"1"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13731","display_name":"Advanced Computing and Algorithms","score":0.895799994468689,"subfield":{"id":"https://openalex.org/subfields/3322","display_name":"Urban Studies"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T13731","display_name":"Advanced Computing and Algorithms","score":0.895799994468689,"subfield":{"id":"https://openalex.org/subfields/3322","display_name":"Urban Studies"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T13579","display_name":"Image and Video Stabilization","score":0.7714999914169312,"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/T12707","display_name":"Vehicle License Plate Recognition","score":0.7347000241279602,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/graffiti","display_name":"Graffiti","score":0.9813722372055054},{"id":"https://openalex.org/keywords/law-enforcement","display_name":"Law enforcement","score":0.6894105672836304},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6198320388793945},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6017702221870422},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5924938917160034},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.5679833889007568},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.5549933910369873},{"id":"https://openalex.org/keywords/interpretation","display_name":"Interpretation (philosophy)","score":0.4947185218334198},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.47841864824295044},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.37570202350616455},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.35165977478027344},{"id":"https://openalex.org/keywords/law","display_name":"Law","score":0.1979590654373169},{"id":"https://openalex.org/keywords/political-science","display_name":"Political science","score":0.11957153677940369}],"concepts":[{"id":"https://openalex.org/C186835682","wikidata":"https://www.wikidata.org/wiki/Q1541559","display_name":"Graffiti","level":2,"score":0.9813722372055054},{"id":"https://openalex.org/C2780262971","wikidata":"https://www.wikidata.org/wiki/Q44554","display_name":"Law enforcement","level":2,"score":0.6894105672836304},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6198320388793945},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6017702221870422},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5924938917160034},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.5679833889007568},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.5549933910369873},{"id":"https://openalex.org/C527412718","wikidata":"https://www.wikidata.org/wiki/Q855395","display_name":"Interpretation (philosophy)","level":2,"score":0.4947185218334198},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.47841864824295044},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37570202350616455},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.35165977478027344},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.1979590654373169},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.11957153677940369},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"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:10.2352/issn.2470-1173.2018.15.coimg-201","is_oa":false,"landing_page_url":"https://doi.org/10.2352/issn.2470-1173.2018.15.coimg-201","pdf_url":null,"source":{"id":"https://openalex.org/S4210227276","display_name":"Electronic Imaging","issn_l":"2470-1173","issn":["2470-1173"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Electronic Imaging","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W638017646","https://openalex.org/W2951480663","https://openalex.org/W4288374578","https://openalex.org/W2914515623","https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W3167935049","https://openalex.org/W3029198973"],"abstract_inverted_index":{"Gangs":[0],"are":[1,40],"a":[2,16,55,67],"serious":[3],"threat":[4],"to":[5,27,60],"the":[6,10,41,62,83],"public":[7],"safety":[8],"in":[9],"United":[11],"States.":[12],"We":[13,65],"have":[14],"developed":[15],"system":[17],"known":[18],"as":[19],"Gang":[20,37],"Graffiti":[21],"Automatic":[22],"Recognition":[23],"and":[24,33,48,75],"Interpretation":[25],"(GARI)":[26],"help":[28],"law":[29],"enforcement":[30],"identify,":[31],"track,":[32],"analyze":[34],"gang":[35],"activities.":[36],"graffiti":[38,43,63],"components":[39],"segmented":[42],"content":[44],"including":[45],"symbols,":[46],"digits,":[47],"characters.":[49],"In":[50],"this":[51],"paper,":[52],"we":[53],"propose":[54],"deep":[56,72],"convolutional":[57],"neural":[58],"network":[59],"classify":[61],"components.":[64],"make":[66],"comparison":[68],"between":[69],"our":[70,76],"proposed":[71,84],"learning":[73],"method":[74,85],"previous":[77],"traditional":[78],"method.":[79],"Experimental":[80],"results":[81],"show":[82],"reaches":[86],"89.3%":[87],"accuracy":[88],"with":[89],"dropout":[90],"regularization.":[91]},"counts_by_year":[{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-31T08:31:51.225901","created_date":"2025-10-10T00:00:00"}