{"id":"https://openalex.org/W2944175223","doi":"https://doi.org/10.23919/elinfocom.2019.8706415","title":"Life Long Across All Four Seasons Scene Understanding","display_name":"Life Long Across All Four Seasons Scene Understanding","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2944175223","doi":"https://doi.org/10.23919/elinfocom.2019.8706415","mag":"2944175223"},"language":"en","primary_location":{"id":"doi:10.23919/elinfocom.2019.8706415","is_oa":false,"landing_page_url":"https://doi.org/10.23919/elinfocom.2019.8706415","pdf_url":null,"source":{"id":"https://openalex.org/S4306498533","display_name":"2019 International Conference on Electronics, Information, and Communication (ICEIC)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Conference on Electronics, Information, and Communication (ICEIC)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5101874415","display_name":"Zhennan Wang","orcid":"https://orcid.org/0000-0002-5814-3798"},"institutions":[{"id":"https://openalex.org/I4210113138","display_name":"Guangzhou Automobile Group (China)","ror":"https://ror.org/026fzn952","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210113138"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhennan Wang","raw_affiliation_strings":["Intelligent Driving Dept., GAC R&D Center, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Intelligent Driving Dept., GAC R&D Center, Guangzhou, China","institution_ids":["https://openalex.org/I4210113138"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101516065","display_name":"Xiang Gao","orcid":"https://orcid.org/0009-0009-5639-8066"},"institutions":[{"id":"https://openalex.org/I4210113138","display_name":"Guangzhou Automobile Group (China)","ror":"https://ror.org/026fzn952","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210113138"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiang Gao","raw_affiliation_strings":["Intelligent Driving Dept., GAC R&D Center, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Intelligent Driving Dept., GAC R&D Center, Guangzhou, China","institution_ids":["https://openalex.org/I4210113138"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035294435","display_name":"Guoyang Xie","orcid":null},"institutions":[{"id":"https://openalex.org/I4210113138","display_name":"Guangzhou Automobile Group (China)","ror":"https://ror.org/026fzn952","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210113138"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guoyang Xie","raw_affiliation_strings":["Intelligent Driving Dept., GAC R&D Center, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Intelligent Driving Dept., GAC R&D Center, Guangzhou, China","institution_ids":["https://openalex.org/I4210113138"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5031172498","display_name":"Jishun Guo","orcid":null},"institutions":[{"id":"https://openalex.org/I4210113138","display_name":"Guangzhou Automobile Group (China)","ror":"https://ror.org/026fzn952","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210113138"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jishun Guo","raw_affiliation_strings":["Intelligent Driving Dept., GAC R&D Center, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Intelligent Driving Dept., GAC R&D Center, Guangzhou, China","institution_ids":["https://openalex.org/I4210113138"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210113138"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.02906595,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9998999834060669,"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":0.9998999834060669,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9990000128746033,"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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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/computer-science","display_name":"Computer science","score":0.7994941473007202},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6466092467308044},{"id":"https://openalex.org/keywords/initialization","display_name":"Initialization","score":0.5226278305053711},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4803522825241089},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4764540493488312},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4727752208709717},{"id":"https://openalex.org/keywords/software-portability","display_name":"Software portability","score":0.4656943082809448},{"id":"https://openalex.org/keywords/partition","display_name":"Partition (number theory)","score":0.4491524398326874},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.44400155544281006},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.4398794174194336},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.4334371089935303},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.4193428158760071},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3948221802711487}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7994941473007202},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6466092467308044},{"id":"https://openalex.org/C114466953","wikidata":"https://www.wikidata.org/wiki/Q6034165","display_name":"Initialization","level":2,"score":0.5226278305053711},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4803522825241089},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4764540493488312},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4727752208709717},{"id":"https://openalex.org/C63000827","wikidata":"https://www.wikidata.org/wiki/Q3080428","display_name":"Software portability","level":2,"score":0.4656943082809448},{"id":"https://openalex.org/C42812","wikidata":"https://www.wikidata.org/wiki/Q1082910","display_name":"Partition (number theory)","level":2,"score":0.4491524398326874},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.44400155544281006},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.4398794174194336},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.4334371089935303},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.4193428158760071},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3948221802711487},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/elinfocom.2019.8706415","is_oa":false,"landing_page_url":"https://doi.org/10.23919/elinfocom.2019.8706415","pdf_url":null,"source":{"id":"https://openalex.org/S4306498533","display_name":"2019 International Conference on Electronics, Information, and Communication (ICEIC)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Conference on Electronics, Information, and Communication (ICEIC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W137456267","https://openalex.org/W1882958252","https://openalex.org/W1903029394","https://openalex.org/W1910657905","https://openalex.org/W1923697677","https://openalex.org/W2124592697","https://openalex.org/W2159291411","https://openalex.org/W2165698076","https://openalex.org/W2172156083","https://openalex.org/W2186094539","https://openalex.org/W2194775991","https://openalex.org/W2412782625","https://openalex.org/W2426267443","https://openalex.org/W2560023338","https://openalex.org/W2563705555","https://openalex.org/W2963826681","https://openalex.org/W2963840672","https://openalex.org/W2963881378","https://openalex.org/W4319988532","https://openalex.org/W6605655187","https://openalex.org/W6639480849","https://openalex.org/W6683633756"],"related_works":["https://openalex.org/W1584537303","https://openalex.org/W2750549761","https://openalex.org/W4388155270","https://openalex.org/W28826848","https://openalex.org/W2122272819","https://openalex.org/W4367156293","https://openalex.org/W1872724644","https://openalex.org/W2130894091","https://openalex.org/W2994151208","https://openalex.org/W4386121542"],"abstract_inverted_index":{"Recently,":[0],"automatous":[1],"driving":[2,14,18],"is":[3,15,149],"grabbing":[4],"everyone's":[5],"attention.":[6],"The":[7,102,138],"technical":[8],"partition":[9],"of":[10,60,109,142,164,194],"the":[11,26,34,81,88,98,106,112,117,134,162,165,175,179,184,192],"automatic":[12],"vehicle":[13],"scene":[16,27,35,46,135],"understanding,":[17],"policy-making":[19],"and":[20,24,54,69,87,115,123],"motion":[21],"control.":[22],"First":[23],"foremost,":[25],"understanding":[28,36,136],"plays":[29],"an":[30],"imperative":[31],"role.":[32],"Meanwhile,":[33],"breaks":[37],"down":[38],"into":[39],"four":[40,62,93,147],"branches,":[41],"which":[42,79,128,160,196],"are":[43,65],"free":[44],"space":[45],"semantic":[47],"segmentation,":[48],"lane":[49],"detection,":[50],"moving":[51,55],"objects":[52,56],"detection":[53],"tracking.":[57],"Main":[58],"challenges":[59,99],"all":[61,92,97,146],"challenging":[63,185],"branches":[64],"unrestricted":[66],"open":[67],"vocabulary":[68],"diverse":[70],"scenes.":[71],"This":[72],"paper":[73],"has":[74],"proposed":[75,103,176],"a":[76,121,130,169],"new":[77],"theory":[78,177],"combines":[80],"improved":[82,167],"fully":[83],"convolutional":[84],"network":[85,154,166],"(iFCN)":[86],"transfer":[89,143],"learning":[90,118,144],"across":[91,145],"seasons":[94],"to":[95,150],"alleviate":[96],"mentioned":[100],"above.":[101],"iFCN":[104],"changes":[105],"traditional":[107],"structure":[108],"FCN":[110],"in":[111],"pooling":[113],"layer":[114],"replaces":[116],"rate":[119],"with":[120,157,191,201],"self-adapted":[122],"much":[124],"more":[125],"reasonable":[126],"one,":[127],"generates":[129],"significant":[131],"improvement":[132,199],"on":[133,183],"assignment.":[137],"global":[139],"prior":[140],"representation":[141],"scenes":[148],"avoid":[151],"training":[152],"entire":[153],"from":[155],"scratch":[156],"random":[158],"initialization,":[159],"makes":[161],"portability":[163],"quite":[168],"lot.":[170],"Experiment":[171],"results":[172],"indicate":[173],"that":[174],"achieves":[178],"state-of-the-art":[180],"mean":[181],"IoU":[182],"GAC":[186],"R&D":[187],"environment":[188],"perception":[189],"benchmark":[190],"value":[193],"86.2%,":[195],"gains":[197],"34.67%":[198],"compared":[200],"conventional":[202],"work.":[203]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}