{"id":"https://openalex.org/W4376480468","doi":"https://doi.org/10.1109/tvt.2023.3275571","title":"MLP-Based Efficient Convolutional Neural Network for Lane Detection","display_name":"MLP-Based Efficient Convolutional Neural Network for Lane Detection","publication_year":2023,"publication_date":"2023-05-12","ids":{"openalex":"https://openalex.org/W4376480468","doi":"https://doi.org/10.1109/tvt.2023.3275571"},"language":"en","primary_location":{"id":"doi:10.1109/tvt.2023.3275571","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tvt.2023.3275571","pdf_url":"https://ieeexplore.ieee.org/ielx7/25/4356907/10123992.pdf","source":{"id":"https://openalex.org/S10936095","display_name":"IEEE Transactions on Vehicular Technology","issn_l":"0018-9545","issn":["0018-9545","1939-9359"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Vehicular Technology","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://ieeexplore.ieee.org/ielx7/25/4356907/10123992.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5031754354","display_name":"Xuedong Yao","orcid":"https://orcid.org/0000-0002-4086-8563"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]},{"id":"https://openalex.org/I4210118728","display_name":"State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing","ror":"https://ror.org/02bpap860","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210118728"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xuedong Yao","raw_affiliation_strings":["State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing (LIESMARS), Wuhan University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing (LIESMARS), Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I4210118728","https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100696368","display_name":"Yandong Wang","orcid":"https://orcid.org/0000-0001-9539-8725"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]},{"id":"https://openalex.org/I4210118728","display_name":"State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing","ror":"https://ror.org/02bpap860","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210118728"]},{"id":"https://openalex.org/I4210119674","display_name":"East China University of Technology","ror":"https://ror.org/027385r44","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210119674"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yandong Wang","raw_affiliation_strings":["State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing (LIESMARS), Wuhan University, Wuhan, China","Collaborative Innovation Center for Geospatial Information Technology, Wuhan, China","Faculty of Geomatics, East China University of Technology, Nanchang, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing (LIESMARS), Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I4210118728","https://openalex.org/I37461747"]},{"raw_affiliation_string":"Collaborative Innovation Center for Geospatial Information Technology, Wuhan, China","institution_ids":[]},{"raw_affiliation_string":"Faculty of Geomatics, East China University of Technology, Nanchang, China","institution_ids":["https://openalex.org/I4210119674"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100458040","display_name":"Yanlan Wu","orcid":"https://orcid.org/0000-0002-8983-3150"},"institutions":[{"id":"https://openalex.org/I143868143","display_name":"Anhui University","ror":"https://ror.org/05th6yx34","country_code":"CN","type":"education","lineage":["https://openalex.org/I143868143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanlan Wu","raw_affiliation_strings":["Information Materials and Intelligent Sensing Laboratory of Anhui Province, Anhui University, Hefei, China","Anhui Engineering Research Center for Geographical Information Intelligent Technology, Hefei, China","School of Resources and Environmental Engineering, Anhui University, Hefei, China"],"affiliations":[{"raw_affiliation_string":"Information Materials and Intelligent Sensing Laboratory of Anhui Province, Anhui University, Hefei, China","institution_ids":["https://openalex.org/I143868143"]},{"raw_affiliation_string":"Anhui Engineering Research Center for Geographical Information Intelligent Technology, Hefei, China","institution_ids":["https://openalex.org/I143868143"]},{"raw_affiliation_string":"School of Resources and Environmental Engineering, Anhui University, Hefei, China","institution_ids":["https://openalex.org/I143868143"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108601527","display_name":"He Guoxiong","orcid":null},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]},{"id":"https://openalex.org/I4210118728","display_name":"State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing","ror":"https://ror.org/02bpap860","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210118728"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guoxiong He","raw_affiliation_strings":["State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing (LIESMARS), Wuhan University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing (LIESMARS), Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I4210118728","https://openalex.org/I37461747"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5061640206","display_name":"Shuchang Luo","orcid":"https://orcid.org/0000-0003-3863-399X"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]},{"id":"https://openalex.org/I4210118728","display_name":"State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing","ror":"https://ror.org/02bpap860","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210118728"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuchang Luo","raw_affiliation_strings":["State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing (LIESMARS), Wuhan University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing (LIESMARS), Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I4210118728","https://openalex.org/I37461747"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5031754354"],"corresponding_institution_ids":["https://openalex.org/I37461747","https://openalex.org/I4210118728"],"apc_list":null,"apc_paid":null,"fwci":1.6752,"has_fulltext":true,"cited_by_count":15,"citation_normalized_percentile":{"value":0.83116672,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"72","issue":"10","first_page":"12602","last_page":"12614"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9998999834060669,"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"}},{"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9940999746322632,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.775459885597229},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.768582820892334},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.6415804624557495},{"id":"https://openalex.org/keywords/computational-complexity-theory","display_name":"Computational complexity theory","score":0.5807475447654724},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5265489220619202},{"id":"https://openalex.org/keywords/multilayer-perceptron","display_name":"Multilayer perceptron","score":0.4984712600708008},{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.49180343747138977},{"id":"https://openalex.org/keywords/locality","display_name":"Locality","score":0.4837922751903534},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.47956007719039917},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.4220835268497467},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.4180299639701843},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.41238734126091003},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3459668755531311},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3435367941856384},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.08727961778640747},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08553072810173035}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.775459885597229},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.768582820892334},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.6415804624557495},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.5807475447654724},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5265489220619202},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.4984712600708008},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.49180343747138977},{"id":"https://openalex.org/C2779808786","wikidata":"https://www.wikidata.org/wiki/Q6664603","display_name":"Locality","level":2,"score":0.4837922751903534},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.47956007719039917},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.4220835268497467},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.4180299639701843},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.41238734126091003},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3459668755531311},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3435367941856384},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.08727961778640747},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08553072810173035},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tvt.2023.3275571","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tvt.2023.3275571","pdf_url":"https://ieeexplore.ieee.org/ielx7/25/4356907/10123992.pdf","source":{"id":"https://openalex.org/S10936095","display_name":"IEEE Transactions on Vehicular Technology","issn_l":"0018-9545","issn":["0018-9545","1939-9359"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Vehicular Technology","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1109/tvt.2023.3275571","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tvt.2023.3275571","pdf_url":"https://ieeexplore.ieee.org/ielx7/25/4356907/10123992.pdf","source":{"id":"https://openalex.org/S10936095","display_name":"IEEE Transactions on Vehicular Technology","issn_l":"0018-9545","issn":["0018-9545","1939-9359"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Vehicular Technology","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G8547973714","display_name":null,"funder_award_id":"41271399","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4376480468.pdf","grobid_xml":"https://content.openalex.org/works/W4376480468.grobid-xml"},"referenced_works_count":78,"referenced_works":["https://openalex.org/W114517082","https://openalex.org/W2051077519","https://openalex.org/W2092282499","https://openalex.org/W2135852591","https://openalex.org/W2146575011","https://openalex.org/W2169886432","https://openalex.org/W2194775991","https://openalex.org/W2211466563","https://openalex.org/W2412782625","https://openalex.org/W2489541753","https://openalex.org/W2573558504","https://openalex.org/W2592939477","https://openalex.org/W2745410201","https://openalex.org/W2752782242","https://openalex.org/W2762439315","https://openalex.org/W2780740184","https://openalex.org/W2781689253","https://openalex.org/W2801378207","https://openalex.org/W2895676856","https://openalex.org/W2899663614","https://openalex.org/W2922509574","https://openalex.org/W2955058313","https://openalex.org/W2962914239","https://openalex.org/W2963091558","https://openalex.org/W2964199920","https://openalex.org/W2971079005","https://openalex.org/W2981441441","https://openalex.org/W2982220924","https://openalex.org/W2995724453","https://openalex.org/W3002702040","https://openalex.org/W3003917023","https://openalex.org/W3025407686","https://openalex.org/W3034985293","https://openalex.org/W3036080349","https://openalex.org/W3045793033","https://openalex.org/W3094502228","https://openalex.org/W3109790059","https://openalex.org/W3111681251","https://openalex.org/W3119586106","https://openalex.org/W3120688202","https://openalex.org/W3126366999","https://openalex.org/W3127751679","https://openalex.org/W3130683545","https://openalex.org/W3157173860","https://openalex.org/W3157506437","https://openalex.org/W3157914380","https://openalex.org/W3173721678","https://openalex.org/W3174350209","https://openalex.org/W3175091786","https://openalex.org/W3185222755","https://openalex.org/W3186979696","https://openalex.org/W3195020967","https://openalex.org/W3197017665","https://openalex.org/W3203848864","https://openalex.org/W3204166336","https://openalex.org/W3206636652","https://openalex.org/W3212723887","https://openalex.org/W3217020292","https://openalex.org/W4200595935","https://openalex.org/W4221143432","https://openalex.org/W4283796844","https://openalex.org/W4293406525","https://openalex.org/W4295934721","https://openalex.org/W4297775537","https://openalex.org/W4312603285","https://openalex.org/W6717372056","https://openalex.org/W6737664043","https://openalex.org/W6739901393","https://openalex.org/W6755977528","https://openalex.org/W6756040250","https://openalex.org/W6781435306","https://openalex.org/W6784333009","https://openalex.org/W6790275670","https://openalex.org/W6795045487","https://openalex.org/W6795140394","https://openalex.org/W6799423381","https://openalex.org/W6802905620","https://openalex.org/W7048330295"],"related_works":["https://openalex.org/W2076543106","https://openalex.org/W2523437662","https://openalex.org/W89844371","https://openalex.org/W2019891950","https://openalex.org/W2085842814","https://openalex.org/W4286643620","https://openalex.org/W4387048144","https://openalex.org/W2492135063","https://openalex.org/W2362514456","https://openalex.org/W2136232598"],"abstract_inverted_index":{"Lane":[0],"detection":[1,71,207],"is":[2,86,161,233],"an":[3,68,82,225,234],"important":[4],"and":[5,102,144,146,175,236],"fundamental":[6],"task":[7],"in":[8,21,35,55,94,123,156,239],"autonomous":[9],"driving.":[10],"Modern":[11],"convolutional":[12,92,139],"neural":[13],"network":[14,96],"(CNN)":[15],"methods":[16,33],"have":[17],"achieved":[18],"high":[19,60],"performance":[20,208],"lane":[22,70,114,183,240],"detection;":[23],"however,":[24],"the":[25,38,90,99,124,129,177,220],"intrinsic":[26],"locality":[27],"of":[28,48,132,169,224,231],"convolution":[29,52,108,232],"operations":[30,53],"makes":[31,176],"these":[32,64],"limited":[34],"effectively":[36],"modeling":[37],"long-range":[39,130],"dependencies":[40,131],"that":[41,194,218],"are":[42,149],"vital":[43],"to":[44,88,97,110,127,152,163],"capture":[45,112,128],"global":[46,154,221],"information":[47,230],"lanes.":[49,133],"Additionally,":[50],"numerous":[51],"result":[54],"considerable":[56],"computational":[57,100,173,201],"cost":[58,101],"for":[59,182],"complexity.":[61],"To":[62],"overcome":[63],"difficulties,":[65],"we":[66,117],"propose":[67],"efficient":[69,181],"method":[72,196],"by":[73],"combining":[74],"CNN":[75],"with":[76,210,227],"a":[77,119,199,205],"multilayer":[78],"perceptron":[79],"(MLP).":[80],"First,":[81],"improved":[83],"bottleneck-1D":[84],"layer":[85,93],"used":[87],"replace":[89],"standard":[91],"overall":[95],"reduce":[98],"parameters":[103],"while":[104,203],"applying":[105],"hybrid":[106,120,135],"dilated":[107],"(HDC)":[109],"better":[111],"multiscale":[113],"information.":[115],"Second,":[116],"construct":[118],"MLP":[121,136,170,226],"block":[122],"latent":[125],"space":[126],"The":[134,167],"projects":[137],"tokenized":[138],"features":[140],"from":[141],"spatial":[142],"locations":[143],"channels,":[145],"then,":[147],"they":[148],"fused":[150],"together":[151],"obtain":[153],"representation,":[155],"which":[157],"each":[158,164],"output":[159],"pixel":[160],"related":[162],"input":[165],"pixel.":[166],"introduction":[168],"further":[171],"decreases":[172],"complexity":[174],"proposed":[178],"architecture":[179],"more":[180],"detection.":[184,241],"Experimental":[185],"results":[186],"on":[187],"two":[188],"challenging":[189],"datasets":[190],"(CULane,":[191],"Tusimple)":[192],"demonstrate":[193],"our":[195],"can":[197],"achieve":[198],"higher":[200],"efficiency":[202],"maintaining":[204],"decent":[206],"compared":[209],"other":[211],"state-of-the-art":[212],"methods.":[213],"Furthermore,":[214],"this":[215],"study":[216],"indicates":[217],"integrating":[219],"representation":[222],"capacity":[223],"local":[228],"prior":[229],"effective":[235],"potential":[237],"perspective":[238]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":1}],"updated_date":"2026-03-27T14:29:43.386196","created_date":"2025-10-10T00:00:00"}