{"id":"https://openalex.org/W6963113058","doi":"https://doi.org/10.21227/wbh6-1k55","title":"Dynamic Scenes Dataset","display_name":"Dynamic Scenes Dataset","publication_year":2019,"publication_date":"2019-04-25","ids":{"openalex":"https://openalex.org/W6963113058","doi":"https://doi.org/10.21227/wbh6-1k55"},"language":"en","primary_location":{"id":"doi:10.21227/wbh6-1k55","is_oa":true,"landing_page_url":"https://doi.org/10.21227/wbh6-1k55","pdf_url":null,"source":{"id":"https://openalex.org/S7407051695","display_name":"IEEE DataPort","issn_l":null,"issn":[],"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","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Dataset"},"type":"dataset","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.21227/wbh6-1k55","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Chen, Haosheng","orcid":"https://orcid.org/0000-0001-6834-2136"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chen, Haosheng","raw_affiliation_strings":["Xiamen University"],"raw_orcid":"https://orcid.org/0000-0001-6834-2136","affiliations":[{"raw_affiliation_string":"Xiamen University","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Zhang, Ge","orcid":null},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhang, Ge","raw_affiliation_strings":["Zhengzhou University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhengzhou University","institution_ids":["https://openalex.org/I38877650"]}]},{"author_position":"last","author":{"id":null,"display_name":"Ye, Yangdong","orcid":null},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ye, Yangdong","raw_affiliation_strings":["Zhengzhou University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhengzhou University","institution_ids":["https://openalex.org/I38877650"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":null,"topics":[],"keywords":[{"id":"https://openalex.org/keywords/closure","display_name":"Closure (psychology)","score":0.3580999970436096},{"id":"https://openalex.org/keywords/loop","display_name":"Loop (graph theory)","score":0.3571000099182129},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.3452000021934509},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.2985999882221222},{"id":"https://openalex.org/keywords/edge-detection","display_name":"Edge detection","score":0.2581000030040741}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6205999851226807},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5752999782562256},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5672000050544739},{"id":"https://openalex.org/C146834321","wikidata":"https://www.wikidata.org/wiki/Q2979672","display_name":"Closure (psychology)","level":2,"score":0.3580999970436096},{"id":"https://openalex.org/C184670325","wikidata":"https://www.wikidata.org/wiki/Q512604","display_name":"Loop (graph theory)","level":2,"score":0.3571000099182129},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.3452000021934509},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.3449000120162964},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2985999882221222},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.2903999984264374},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.28220000863075256},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.2743000090122223},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.2741999924182892},{"id":"https://openalex.org/C193536780","wikidata":"https://www.wikidata.org/wiki/Q1513153","display_name":"Edge detection","level":4,"score":0.2581000030040741},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.2538999915122986},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2533999979496002}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.21227/wbh6-1k55","is_oa":true,"landing_page_url":"https://doi.org/10.21227/wbh6-1k55","pdf_url":null,"source":{"id":"https://openalex.org/S7407051695","display_name":"IEEE DataPort","issn_l":null,"issn":[],"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","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Dataset"}],"best_oa_location":{"id":"doi:10.21227/wbh6-1k55","is_oa":true,"landing_page_url":"https://doi.org/10.21227/wbh6-1k55","pdf_url":null,"source":{"id":"https://openalex.org/S7407051695","display_name":"IEEE DataPort","issn_l":null,"issn":[],"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","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Dataset"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.7955799698829651}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0,46,59,77],"\"Dynamic":[1],"Scenes\"":[2],"Dataset":[3],"is":[4,91],"provided":[5],"for":[6],"testing":[7],"visual":[8],"loop":[9],"closure":[10],"detection":[11],"algorithms":[12],"in":[13,22,34,55],"highly":[14],"dynamic":[15],"scenes.":[16],"It":[17],"has":[18],"a":[19,40,68,87],"strong":[20],"background":[21],"some":[23],"crucial":[24],"applications":[25],"such":[26],"as":[27,53,70],"autonomous":[28],"driving":[29],"systems.The":[30],"dataset":[31,49],"was":[32,63,82],"captured":[33],"the":[35,56,71,94],"central":[36],"commercial":[37],"district":[38],"of":[39,42],"city":[41],"ten":[43],"million":[44],"people.":[45],"\u201cDynamic":[47],"Scenes\u201d":[48],"contains":[50],"two":[51],"sequences":[52],"shown":[54],"figure":[57],"above.":[58],"first":[60],"one,":[61],"which":[62],"acquired":[64,83],"by":[65,84,93],"traveling":[66,85],"around":[67,86],"lake":[69],"blue":[72],"trajectory,":[73],"named":[74,80],"\u201cRoad":[75],"Ring.\u201d":[76],"other":[78],"sequence,":[79],"\u201cCBD,\u201d":[81],"business":[88],"district,":[89],"and":[90,96],"depicted":[92],"red":[95],"green":[97],"trajectories.":[98]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2025-10-10T00:00:00"}