{"id":"https://openalex.org/W4407467181","doi":"https://doi.org/10.1109/iccvit63928.2024.10872605","title":"Semantic Segmentation Method for Drivable Areas under Unstructured Road","display_name":"Semantic Segmentation Method for Drivable Areas under Unstructured Road","publication_year":2024,"publication_date":"2024-11-24","ids":{"openalex":"https://openalex.org/W4407467181","doi":"https://doi.org/10.1109/iccvit63928.2024.10872605"},"language":"en","primary_location":{"id":"doi:10.1109/iccvit63928.2024.10872605","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccvit63928.2024.10872605","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 2nd International Conference on Computer, Vision and Intelligent Technology (ICCVIT)","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/A5074641200","display_name":"Faming Zhang","orcid":"https://orcid.org/0000-0003-4157-1144"},"institutions":[{"id":"https://openalex.org/I114234892","display_name":"Beijing Union University","ror":"https://ror.org/01hg31662","country_code":"CN","type":"education","lineage":["https://openalex.org/I114234892"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ting Zhang","raw_affiliation_strings":["Beijing Union University,Beijing Key Laboratory of Information Service Engineering,Beijing,China,100101"],"affiliations":[{"raw_affiliation_string":"Beijing Union University,Beijing Key Laboratory of Information Service Engineering,Beijing,China,100101","institution_ids":["https://openalex.org/I114234892"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018620403","display_name":"Yuansheng Liu","orcid":"https://orcid.org/0000-0002-7680-3155"},"institutions":[{"id":"https://openalex.org/I114234892","display_name":"Beijing Union University","ror":"https://ror.org/01hg31662","country_code":"CN","type":"education","lineage":["https://openalex.org/I114234892"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuansheng Liu","raw_affiliation_strings":["Beijing Union University,College of Robotics,Beijing,China,100101"],"affiliations":[{"raw_affiliation_string":"Beijing Union University,College of Robotics,Beijing,China,100101","institution_ids":["https://openalex.org/I114234892"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5074641200"],"corresponding_institution_ids":["https://openalex.org/I114234892"],"apc_list":null,"apc_paid":null,"fwci":0.6989,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.73737557,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14270","display_name":"Simulation and Modeling Applications","score":0.6901000142097473,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T14270","display_name":"Simulation and Modeling Applications","score":0.6901000142097473,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T13734","display_name":"Advanced Computational Techniques and Applications","score":0.6797999739646912,"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/T13832","display_name":"Advanced Decision-Making Techniques","score":0.654699981212616,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7709102034568787},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5584210753440857},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5553688406944275},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5531663298606873},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4939475655555725},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.37778475880622864},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3410293459892273}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7709102034568787},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5584210753440857},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5553688406944275},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5531663298606873},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4939475655555725},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.37778475880622864},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3410293459892273}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccvit63928.2024.10872605","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccvit63928.2024.10872605","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 2nd International Conference on Computer, Vision and Intelligent Technology (ICCVIT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1903029394","https://openalex.org/W2412782625","https://openalex.org/W2886934227","https://openalex.org/W3169865585","https://openalex.org/W4289752563","https://openalex.org/W4312443924","https://openalex.org/W4386076267","https://openalex.org/W6696085341","https://openalex.org/W6789654255","https://openalex.org/W6846053352","https://openalex.org/W6850929176","https://openalex.org/W6987786997"],"related_works":["https://openalex.org/W4379231730","https://openalex.org/W4389858081","https://openalex.org/W2501551404","https://openalex.org/W4298131179","https://openalex.org/W2113201962","https://openalex.org/W4385583601","https://openalex.org/W4395685956","https://openalex.org/W3159516372","https://openalex.org/W4398146871","https://openalex.org/W1522196789"],"abstract_inverted_index":{"To":[0],"improve":[1],"the":[2,24,34,59,76,107,115,125,129,145],"ability":[3],"of":[4,33,112,144],"autonomous":[5],"vehicles":[6],"to":[7,67,80,142],"recognize":[8],"drivable":[9,88],"areas":[10],"on":[11,23,114,131],"park":[12,92],"roads,":[13],"this":[14,31],"study":[15],"puts":[16],"foward":[17],"a":[18,37,49,110,119,135],"semantic":[19],"segmentation":[20,90],"approach":[21],"based":[22],"STDC":[25,35,126,146],"(Short-Term":[26],"Dense":[27],"Connection)":[28],"network.":[29,127,147],"On":[30],"foundation":[32],"network,":[36],"deep":[38],"convolutional":[39],"neural":[40],"network":[41],"with":[42],"an":[43],"encoder-decoder":[44],"structure":[45],"is":[46,56,65],"designed,":[47],"and":[48,71,96,100],"double-chain":[50],"cascaded":[51],"feature":[52],"fusion":[53],"module":[54],"(DCFFM)":[55],"introduced.":[57],"Additionally,":[58],"Convolutional":[60],"Block":[61],"Attention":[62],"Module":[63],"(CBAM)":[64],"incorporated":[66],"dynamically":[68],"adjust":[69],"channel":[70],"spatial":[72],"attention,":[73],"thereby":[74],"reinforcing":[75],"model":[77],"s":[78],"capacity":[79],"discern":[81],"crucial":[82],"features.":[83],"A":[84],"dataset":[85],"suitable":[86],"for":[87,98],"area":[89],"in":[91,140],"environments":[93],"was":[94],"collected":[95],"used":[97],"training":[99],"validation.":[101],"The":[102],"experimental":[103],"outcomes":[104],"demonstrate":[105],"that":[106,143],"algorithm":[108],"attained":[109],"mIoU":[111,130],"98.41%":[113],"self-built":[116],"dataset,":[117],"representing":[118],"2.73":[120],"percentage":[121,137],"point":[122,138],"improvement":[123],"over":[124],"Furthermore,":[128],"public":[132],"datasets":[133],"exhibited":[134],"2.55":[136],"enhancement":[139],"comparison":[141]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2025-12-19T19:40:27.379048","created_date":"2025-10-10T00:00:00"}