{"id":"https://openalex.org/W4220667029","doi":"https://doi.org/10.3390/e24040466","title":"HMD-Net: A Vehicle Hazmat Marker Detection Benchmark","display_name":"HMD-Net: A Vehicle Hazmat Marker Detection Benchmark","publication_year":2022,"publication_date":"2022-03-28","ids":{"openalex":"https://openalex.org/W4220667029","doi":"https://doi.org/10.3390/e24040466","pmid":"https://pubmed.ncbi.nlm.nih.gov/35455129"},"language":"en","primary_location":{"id":"doi:10.3390/e24040466","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e24040466","pdf_url":"https://www.mdpi.com/1099-4300/24/4/466/pdf?version=1648455281","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"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":"Entropy","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/1099-4300/24/4/466/pdf?version=1648455281","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5060296003","display_name":"Lei Jia","orcid":"https://orcid.org/0000-0003-0192-825X"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Jia","raw_affiliation_strings":["Beijing Key Lab of Traffic Data Analysis and Mining, Beijing Jiaotong University, Beijing 100044, China"],"raw_orcid":"https://orcid.org/0000-0003-0192-825X","affiliations":[{"raw_affiliation_string":"Beijing Key Lab of Traffic Data Analysis and Mining, Beijing Jiaotong University, Beijing 100044, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035711905","display_name":"Jianzhu Wang","orcid":"https://orcid.org/0000-0001-9085-3848"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianzhu Wang","raw_affiliation_strings":["Beijing Key Lab of Traffic Data Analysis and Mining, Beijing Jiaotong University, Beijing 100044, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Key Lab of Traffic Data Analysis and Mining, Beijing Jiaotong University, Beijing 100044, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101518382","display_name":"Tianyuan Wang","orcid":"https://orcid.org/0000-0001-5866-3577"},"institutions":[{"id":"https://openalex.org/I4387154941","display_name":"Shenzhen Urban Transport Planning Center Co.","ror":"https://ror.org/009q8er18","country_code":null,"type":"company","lineage":["https://openalex.org/I4387154941"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianyuan Wang","raw_affiliation_strings":["Shenzhen Urban Transport Planning Center Co., Ltd., Shenzhen 518000, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenzhen Urban Transport Planning Center Co., Ltd., Shenzhen 518000, China","institution_ids":["https://openalex.org/I4387154941"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101617347","display_name":"Xiaobao Li","orcid":"https://orcid.org/0000-0002-4088-0060"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaobao Li","raw_affiliation_strings":["Beijing Key Lab of Traffic Data Analysis and Mining, Beijing Jiaotong University, Beijing 100044, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Key Lab of Traffic Data Analysis and Mining, Beijing Jiaotong University, Beijing 100044, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103975844","display_name":"Haomin Yu","orcid":null},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haomin Yu","raw_affiliation_strings":["Beijing Key Lab of Traffic Data Analysis and Mining, Beijing Jiaotong University, Beijing 100044, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Key Lab of Traffic Data Analysis and Mining, Beijing Jiaotong University, Beijing 100044, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005350496","display_name":"Qingyong Li","orcid":"https://orcid.org/0000-0002-3860-4809"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Qingyong Li","raw_affiliation_strings":["Beijing Key Lab of Traffic Data Analysis and Mining, Beijing Jiaotong University, Beijing 100044, China"],"raw_orcid":"https://orcid.org/0000-0002-3860-4809","affiliations":[{"raw_affiliation_string":"Beijing Key Lab of Traffic Data Analysis and Mining, Beijing Jiaotong University, Beijing 100044, China","institution_ids":["https://openalex.org/I21193070"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5005350496"],"corresponding_institution_ids":["https://openalex.org/I21193070"],"apc_list":{"value":2000,"currency":"CHF","value_usd":2227},"apc_paid":{"value":2000,"currency":"CHF","value_usd":2227},"fwci":0.2428,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.44254576,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":96},"biblio":{"volume":"24","issue":"4","first_page":"466","last_page":"466"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9995999932289124,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9995999932289124,"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":0.9988999962806702,"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"}},{"id":"https://openalex.org/T12707","display_name":"Vehicle License Plate Recognition","score":0.998199999332428,"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/computer-science","display_name":"Computer science","score":0.7607080936431885},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6151137948036194},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.49193811416625977},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4914811849594116},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.4429191052913666},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.4388739764690399},{"id":"https://openalex.org/keywords/benchmarking","display_name":"Benchmarking","score":0.4185212254524231},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.40125492215156555},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.39173653721809387},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.13079240918159485},{"id":"https://openalex.org/keywords/systems-engineering","display_name":"Systems engineering","score":0.09555095434188843}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7607080936431885},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6151137948036194},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.49193811416625977},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4914811849594116},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.4429191052913666},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.4388739764690399},{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.4185212254524231},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40125492215156555},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.39173653721809387},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.13079240918159485},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.09555095434188843},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.0},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","level":1,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.3390/e24040466","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e24040466","pdf_url":"https://www.mdpi.com/1099-4300/24/4/466/pdf?version=1648455281","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"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":"Entropy","raw_type":"journal-article"},{"id":"pmid:35455129","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35455129","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":"Entropy (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:9029883","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9029883","pdf_url":null,"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":"Entropy (Basel)","raw_type":"Text"},{"id":"pmh:oai:doaj.org/article:a369e59f40b74ed3970c175a1b808705","is_oa":true,"landing_page_url":"https://doaj.org/article/a369e59f40b74ed3970c175a1b808705","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":"Entropy, Vol 24, Iss 4, p 466 (2022)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1099-4300/24/4/466/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/e24040466","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"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":"Entropy; Volume 24; Issue 4; Pages: 466","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/e24040466","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e24040466","pdf_url":"https://www.mdpi.com/1099-4300/24/4/466/pdf?version=1648455281","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"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":"Entropy","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4220667029.pdf","grobid_xml":"https://content.openalex.org/works/W4220667029.grobid-xml"},"referenced_works_count":39,"referenced_works":["https://openalex.org/W1536680647","https://openalex.org/W1836465849","https://openalex.org/W1902934009","https://openalex.org/W2044672230","https://openalex.org/W2073704637","https://openalex.org/W2102605133","https://openalex.org/W2109255472","https://openalex.org/W2167215970","https://openalex.org/W2194775991","https://openalex.org/W2309015593","https://openalex.org/W2504335775","https://openalex.org/W2523969920","https://openalex.org/W2565639579","https://openalex.org/W2570343428","https://openalex.org/W2612930051","https://openalex.org/W2613718673","https://openalex.org/W2783152060","https://openalex.org/W2962851801","https://openalex.org/W2963037989","https://openalex.org/W2963163009","https://openalex.org/W2963579094","https://openalex.org/W2963857746","https://openalex.org/W2974152701","https://openalex.org/W2990308371","https://openalex.org/W2997747012","https://openalex.org/W3041118858","https://openalex.org/W3042011474","https://openalex.org/W3109202794","https://openalex.org/W3159178685","https://openalex.org/W3167308647","https://openalex.org/W3181581708","https://openalex.org/W3205426545","https://openalex.org/W3213037371","https://openalex.org/W4285557518","https://openalex.org/W6677103964","https://openalex.org/W6737437461","https://openalex.org/W6745136726","https://openalex.org/W6762585180","https://openalex.org/W6798233776"],"related_works":["https://openalex.org/W4238897586","https://openalex.org/W435179959","https://openalex.org/W2619091065","https://openalex.org/W2059640416","https://openalex.org/W1490753184","https://openalex.org/W2284465472","https://openalex.org/W2291782699","https://openalex.org/W1993948687","https://openalex.org/W2011676020","https://openalex.org/W2770764537"],"abstract_inverted_index":{"Vehicles":[0],"carrying":[1],"hazardous":[2],"material":[3],"(hazmat)":[4],"are":[5],"severe":[6],"threats":[7],"to":[8],"the":[9,43,110,148,152],"safety":[10],"of":[11,45,70],"highway":[12],"transportation,":[13],"and":[14,100,137,151],"a":[15,55,68,80,96,108,117,144],"model":[16],"that":[17,124],"can":[18,112,142],"automatically":[19],"recognize":[20],"hazmat":[21,46,58,72,88],"markers":[22,73],"installed":[23],"or":[24],"attached":[25],"on":[26,116],"vehicles":[27],"is":[28,36,101],"essential":[29],"for":[30,41],"intelligent":[31],"management":[32],"systems.":[33],"However,":[34],"there":[35],"still":[37],"no":[38],"public":[39],"dataset":[40,60],"benchmarking":[42],"task":[44],"marker":[47,59,89],"detection.":[48],"To":[49],"this":[50,52],"end,":[51],"paper":[53],"releases":[54],"large-scale":[56],"vehicle":[57],"named":[61,92],"VisInt-VHM,":[62],"which":[63,94],"includes":[64],"10,000":[65],"images":[66],"with":[67,126],"total":[69],"20,023":[71],"captured":[74],"under":[75],"different":[76],"environmental":[77],"conditions":[78],"from":[79],"real-world":[81],"highway.":[82],"Meanwhile,":[83],"we":[84],"provide":[85],"an":[86],"compact":[87],"detection":[90,149],"network":[91],"HMD-Net,":[93],"utilizes":[95],"revised":[97],"lightweight":[98,135,139],"backbone":[99],"further":[102],"compressed":[103],"by":[104],"channel":[105],"pruning.":[106],"As":[107],"consequence,":[109],"trained-model":[111],"be":[113],"efficiently":[114],"deployed":[115],"resource-restricted":[118],"edge":[119],"device.":[120],"Experimental":[121],"results":[122],"demonstrate":[123],"compared":[125],"some":[127],"established":[128],"methods":[129],"such":[130],"as":[131],"YOLOv3,":[132],"YOLOv4,":[133],"their":[134],"versions":[136],"popular":[138],"models,":[140],"HMD-Net":[141],"achieve":[143],"better":[145],"trade-off":[146],"between":[147],"accuracy":[150],"inference":[153],"speed.":[154]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":2}],"updated_date":"2026-08-11T07:18:39.950985","created_date":"2025-10-10T00:00:00"}
