{"id":"https://openalex.org/W4389298072","doi":"https://doi.org/10.3390/s23239607","title":"Zero-Shot Traffic Sign Recognition Based on Midlevel Feature Matching","display_name":"Zero-Shot Traffic Sign Recognition Based on Midlevel Feature Matching","publication_year":2023,"publication_date":"2023-12-04","ids":{"openalex":"https://openalex.org/W4389298072","doi":"https://doi.org/10.3390/s23239607","pmid":"https://pubmed.ncbi.nlm.nih.gov/38067982"},"language":"en","primary_location":{"id":"doi:10.3390/s23239607","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s23239607","pdf_url":"https://www.mdpi.com/1424-8220/23/23/9607/pdf?version=1701700084","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/23/23/9607/pdf?version=1701700084","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5038719961","display_name":"Yaozong Gan","orcid":"https://orcid.org/0009-0001-8813-3400"},"institutions":[{"id":"https://openalex.org/I205349734","display_name":"Hokkaido University","ror":"https://ror.org/02e16g702","country_code":"JP","type":"education","lineage":["https://openalex.org/I205349734"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yaozong Gan","raw_affiliation_strings":["Graduate School of Information Science and Technology, Hokkaido University, N-14, W-9, Kita-ku, Sapporo 060-0814, Japan"],"raw_orcid":"https://orcid.org/0009-0001-8813-3400","affiliations":[{"raw_affiliation_string":"Graduate School of Information Science and Technology, Hokkaido University, N-14, W-9, Kita-ku, Sapporo 060-0814, Japan","institution_ids":["https://openalex.org/I205349734"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100406322","display_name":"Guang Li","orcid":"https://orcid.org/0000-0003-2898-2504"},"institutions":[{"id":"https://openalex.org/I205349734","display_name":"Hokkaido University","ror":"https://ror.org/02e16g702","country_code":"JP","type":"education","lineage":["https://openalex.org/I205349734"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Guang Li","raw_affiliation_strings":["Education and Research Center for Mathematical and Data Science, Hokkaido University, N-12, W-7, Kita-Ku, Sapporo 060-0812, Japan"],"raw_orcid":"https://orcid.org/0000-0003-2898-2504","affiliations":[{"raw_affiliation_string":"Education and Research Center for Mathematical and Data Science, Hokkaido University, N-12, W-7, Kita-Ku, Sapporo 060-0812, Japan","institution_ids":["https://openalex.org/I205349734"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002757875","display_name":"Ren Togo","orcid":"https://orcid.org/0000-0002-4474-3995"},"institutions":[{"id":"https://openalex.org/I205349734","display_name":"Hokkaido University","ror":"https://ror.org/02e16g702","country_code":"JP","type":"education","lineage":["https://openalex.org/I205349734"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Ren Togo","raw_affiliation_strings":["Faculty of Information Science and Technology, Hokkaido University, N-14, W-9, Kita-ku, Sapporo 060-0814, Japan"],"raw_orcid":"https://orcid.org/0000-0002-4474-3995","affiliations":[{"raw_affiliation_string":"Faculty of Information Science and Technology, Hokkaido University, N-14, W-9, Kita-ku, Sapporo 060-0814, Japan","institution_ids":["https://openalex.org/I205349734"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033215072","display_name":"Keisuke Maeda","orcid":"https://orcid.org/0000-0001-8039-3462"},"institutions":[{"id":"https://openalex.org/I205349734","display_name":"Hokkaido University","ror":"https://ror.org/02e16g702","country_code":"JP","type":"education","lineage":["https://openalex.org/I205349734"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Keisuke Maeda","raw_affiliation_strings":["Faculty of Information Science and Technology, Hokkaido University, N-14, W-9, Kita-ku, Sapporo 060-0814, Japan"],"raw_orcid":"https://orcid.org/0000-0001-8039-3462","affiliations":[{"raw_affiliation_string":"Faculty of Information Science and Technology, Hokkaido University, N-14, W-9, Kita-ku, Sapporo 060-0814, Japan","institution_ids":["https://openalex.org/I205349734"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009032240","display_name":"Takahiro Ogawa","orcid":"https://orcid.org/0000-0001-5332-8112"},"institutions":[{"id":"https://openalex.org/I205349734","display_name":"Hokkaido University","ror":"https://ror.org/02e16g702","country_code":"JP","type":"education","lineage":["https://openalex.org/I205349734"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Takahiro Ogawa","raw_affiliation_strings":["Faculty of Information Science and Technology, Hokkaido University, N-14, W-9, Kita-ku, Sapporo 060-0814, Japan"],"raw_orcid":"https://orcid.org/0000-0001-5332-8112","affiliations":[{"raw_affiliation_string":"Faculty of Information Science and Technology, Hokkaido University, N-14, W-9, Kita-ku, Sapporo 060-0814, Japan","institution_ids":["https://openalex.org/I205349734"]}]},{"author_position":"last","author":{"id":null,"display_name":"Miki Haseyama","orcid":"https://orcid.org/0000-0003-1496-1761"},"institutions":[{"id":"https://openalex.org/I205349734","display_name":"Hokkaido University","ror":"https://ror.org/02e16g702","country_code":"JP","type":"education","lineage":["https://openalex.org/I205349734"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Miki Haseyama","raw_affiliation_strings":["Faculty of Information Science and Technology, Hokkaido University, N-14, W-9, Kita-ku, Sapporo 060-0814, Japan"],"raw_orcid":"https://orcid.org/0000-0003-1496-1761","affiliations":[{"raw_affiliation_string":"Faculty of Information Science and Technology, Hokkaido University, N-14, W-9, Kita-ku, Sapporo 060-0814, Japan","institution_ids":["https://openalex.org/I205349734"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I205349734"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2673},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2673},"fwci":1.4024,"has_fulltext":true,"cited_by_count":11,"citation_normalized_percentile":{"value":0.81593928,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":"23","issue":"23","first_page":"9607","last_page":"9607"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11398","display_name":"Hand Gesture Recognition Systems","score":0.9958000183105469,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/T11398","display_name":"Hand Gesture Recognition Systems","score":0.9958000183105469,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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":0.9944999814033508,"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/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.9940999746322632,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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/traffic-sign-recognition","display_name":"Traffic sign recognition","score":0.9256380796432495},{"id":"https://openalex.org/keywords/traffic-sign","display_name":"Traffic sign","score":0.7804298400878906},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7251771092414856},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6952266693115234},{"id":"https://openalex.org/keywords/sign","display_name":"Sign (mathematics)","score":0.565231442451477},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.5356741547584534},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5356077551841736},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5340202450752258},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.514814555644989},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.47205930948257446},{"id":"https://openalex.org/keywords/sign-language","display_name":"Sign language","score":0.41877469420433044},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.05970132350921631}],"concepts":[{"id":"https://openalex.org/C6528762","wikidata":"https://www.wikidata.org/wiki/Q1574298","display_name":"Traffic sign recognition","level":4,"score":0.9256380796432495},{"id":"https://openalex.org/C2983860417","wikidata":"https://www.wikidata.org/wiki/Q170285","display_name":"Traffic sign","level":3,"score":0.7804298400878906},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7251771092414856},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6952266693115234},{"id":"https://openalex.org/C139676723","wikidata":"https://www.wikidata.org/wiki/Q1193832","display_name":"Sign (mathematics)","level":2,"score":0.565231442451477},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5356741547584534},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5356077551841736},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5340202450752258},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.514814555644989},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.47205930948257446},{"id":"https://openalex.org/C522192633","wikidata":"https://www.wikidata.org/wiki/Q34228","display_name":"Sign language","level":2,"score":0.41877469420433044},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.05970132350921631},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","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/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","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/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":6,"locations":[{"id":"doi:10.3390/s23239607","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s23239607","pdf_url":"https://www.mdpi.com/1424-8220/23/23/9607/pdf?version=1701700084","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},{"id":"pmid:38067982","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/38067982","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:10708787","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/10708787","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC10708787/pdf/sensors-23-09607.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors (Basel)","raw_type":"Text"},{"id":"pmh:oai:doaj.org/article:78becdf2de7042e4a9b6a1e2d749bcf4","is_oa":true,"landing_page_url":"https://doaj.org/article/78becdf2de7042e4a9b6a1e2d749bcf4","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors, Vol 23, Iss 23, p 9607 (2023)","raw_type":"article"},{"id":"pmh:oai:eprints.lib.hokudai.ac.jp:2115/91129","is_oa":false,"landing_page_url":"http://hdl.handle.net/2115/91129","pdf_url":null,"source":{"id":"https://openalex.org/S4306400549","display_name":"Hokkaido University Collection of Scholarly and Academic Papers (Hokkaido University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205349734","host_organization_name":"Hokkaido University","host_organization_lineage":["https://openalex.org/I205349734"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"article"},{"id":"pmh:oai:irdb.nii.ac.jp:01364:0007201975","is_oa":false,"landing_page_url":"https://hdl.handle.net/2115/91129","pdf_url":null,"source":{"id":"https://openalex.org/S7407056385","display_name":"Institutional Repositories DataBase (IRDB)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I184597095","host_organization_name":"National Institute of Informatics","host_organization_lineage":["https://openalex.org/I184597095"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors","raw_type":"journal article"}],"best_oa_location":{"id":"doi:10.3390/s23239607","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s23239607","pdf_url":"https://www.mdpi.com/1424-8220/23/23/9607/pdf?version=1701700084","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.6700000166893005,"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3"}],"awards":[{"id":"https://openalex.org/G1489392204","display_name":null,"funder_award_id":"JPMJFS2101","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G3586487095","display_name":"Construction of ultra-low-volume anonymous learning technology and universal learning technology to improve the versatility of medical AI","funder_award_id":"23K11141","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G4092381066","display_name":"General-purpose deep learning theory for ultra-low computational complexity and low capacity in the age of edge AI","funder_award_id":"23K21676","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G4506063253","display_name":null,"funder_award_id":"JP21H03456","funder_id":"https://openalex.org/F4320334789","funder_display_name":"Japan Science and Technology Agency"},{"id":"https://openalex.org/G4562627959","display_name":"\u753b\u50cf\u8a8d\u8b58\u306e\u9ad8\u5ea6\u5316\u306b\u5411\u3051\u305f\u753b\u50cf\u306e\u64ae\u5f71\u65b9\u6cd5\u3092\u6700\u9069\u5316\u3059\u308b\u7570\u74b0\u5883\u7570\u7a2e\u30c7\u30fc\u30bf\u9069\u5fdc\u578bAI\u306e\u69cb\u7bc9","funder_award_id":"23K11211","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G7143781540","display_name":null,"funder_award_id":"JPMJFS2101","funder_id":"https://openalex.org/F4320334789","funder_display_name":"Japan Science and Technology Agency"},{"id":"https://openalex.org/G862958931","display_name":null,"funder_award_id":"JPMJFS2101","funder_id":"https://openalex.org/F2726011503","funder_display_name":"University Fellowship Creation Project for Creating Scientific and Technological Innovation"},{"id":"https://openalex.org/G8739887802","display_name":null,"funder_award_id":"JP21H03456","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"}],"funders":[{"id":"https://openalex.org/F2726011503","display_name":"University Fellowship Creation Project for Creating Scientific and Technological Innovation","ror":null},{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"},{"id":"https://openalex.org/F4320334789","display_name":"Japan Science and Technology Agency","ror":"https://ror.org/00097mb19"}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4389298072.pdf"},"referenced_works_count":55,"referenced_works":["https://openalex.org/W659495306","https://openalex.org/W1536680647","https://openalex.org/W1677409904","https://openalex.org/W1895191496","https://openalex.org/W1977610018","https://openalex.org/W2065429801","https://openalex.org/W2067713319","https://openalex.org/W2077319423","https://openalex.org/W2079854881","https://openalex.org/W2108598243","https://openalex.org/W2111502429","https://openalex.org/W2112796928","https://openalex.org/W2121420859","https://openalex.org/W2124386111","https://openalex.org/W2126628495","https://openalex.org/W2141125852","https://openalex.org/W2150581781","https://openalex.org/W2151049637","https://openalex.org/W2151686145","https://openalex.org/W2163605009","https://openalex.org/W2194775991","https://openalex.org/W2472350142","https://openalex.org/W2726204845","https://openalex.org/W2790196784","https://openalex.org/W2808910047","https://openalex.org/W2891619122","https://openalex.org/W2898734513","https://openalex.org/W2943659362","https://openalex.org/W2955797710","https://openalex.org/W2962723485","https://openalex.org/W2975886832","https://openalex.org/W2982595670","https://openalex.org/W2996919757","https://openalex.org/W3001261202","https://openalex.org/W3009899240","https://openalex.org/W3012027440","https://openalex.org/W3044795413","https://openalex.org/W3119096589","https://openalex.org/W3132476814","https://openalex.org/W3157288834","https://openalex.org/W3159384598","https://openalex.org/W3159943573","https://openalex.org/W3193943785","https://openalex.org/W3216320999","https://openalex.org/W4205139138","https://openalex.org/W4206510012","https://openalex.org/W4220773165","https://openalex.org/W4282049157","https://openalex.org/W4293191395","https://openalex.org/W4318147428","https://openalex.org/W4318777819","https://openalex.org/W6683411478","https://openalex.org/W6684191040","https://openalex.org/W6729025473","https://openalex.org/W6838393215"],"related_works":["https://openalex.org/W4382897155","https://openalex.org/W4283820116","https://openalex.org/W4379231512","https://openalex.org/W4378699879","https://openalex.org/W3128164723","https://openalex.org/W4286647459","https://openalex.org/W4309650776","https://openalex.org/W4386037136","https://openalex.org/W3021119405","https://openalex.org/W4206608251"],"abstract_inverted_index":{"Traffic":[0,167],"sign":[1,27,52,84,94,106,121,155],"recognition":[2,28,38,107,162],"is":[3,68],"a":[4,45,69,92,174],"complex":[5],"and":[6,18,34,66,118,173],"challenging":[7],"yet":[8],"popular":[9],"problem":[10],"that":[11,146],"can":[12,35,103],"assist":[13],"drivers":[14],"on":[15,164],"the":[16,55,114,126,150,165],"road":[17],"reduce":[19],"traffic":[20,26,51,60,72,83,93,105,120,137,154],"accidents.":[21],"Most":[22],"existing":[23],"methods":[24,42,75],"for":[25,54,97],"use":[29],"convolutional":[30],"neural":[31],"networks":[32],"(CNNs)":[33],"achieve":[36],"high":[37],"accuracy.":[39],"However,":[40],"these":[41,74,88],"first":[43],"require":[44],"large":[46],"number":[47],"of":[48,71,116,129,136,152],"carefully":[49],"crafted":[50],"datasets":[53],"training":[56,109,141],"process.":[57],"Moreover,":[58],"since":[59],"signs":[61,138],"differ":[62],"in":[63],"each":[64],"country":[65],"there":[67],"variety":[70],"signs,":[73],"need":[76],"to":[77,131],"be":[78],"fine-tuned":[79],"when":[80],"recognizing":[81],"new":[82],"categories.":[85],"To":[86],"address":[87],"issues,":[89],"we":[90],"propose":[91],"matching":[95,113],"method":[96,102,124,159],"zero-shot":[98,153],"recognition.":[99,156],"Our":[100,123],"proposed":[101,158],"perform":[104],"without":[108,139],"data":[110],"by":[111],"directly":[112],"similarity":[115],"target":[117],"template":[119],"images.":[122],"uses":[125],"midlevel":[127,147],"features":[128,148],"CNNs":[130],"obtain":[132],"robust":[133],"feature":[134],"representations":[135],"additional":[140],"or":[142],"fine-tuning.":[143],"We":[144],"discovered":[145],"improve":[149],"accuracy":[151],"The":[157],"achieves":[160],"promising":[161],"results":[163],"German":[166],"Sign":[168],"Recognition":[169],"Benchmark":[170],"open":[171],"dataset":[172,176],"real-world":[175],"taken":[177],"from":[178],"Sapporo":[179],"City,":[180],"Japan.":[181]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":6}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}
