乐胖代购免代理版

{"id":"https://openalex.org/W2993559917","doi":"https://doi.org/10.1109/ispacs.2018.8923499","title":"Enhanced Depth Estimation for Light Field Cameras by Variable-Patch-Size Tensor Extraction","display_name":"Enhanced Depth Estimation for Light Field Cameras by Variable-Patch-Size Tensor Extraction","publication_year":2018,"publication_date":"2018-11-01","ids":{"openalex":"https://openalex.org/W2993559917","doi":"https://doi.org/10.1109/ispacs.2018.8923499","mag":"2993559917"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/ispacs.2018.8923499","pdf_url":null,"source":{"id":"https://openalex.org/S4363605678","display_name":"2021 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_indexed_in_scopus":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":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"proceedings-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/A5012395425","display_name":"Junke Li","orcid":"https://orcid.org/0000-0002-9957-5650"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"funder","lineage":["https://openalex.org/I99065089"]},{"id":"https://openalex.org/I3131625388","display_name":"University Town of Shenzhen","ror":"https://ror.org/05f5j6225","country_code":"CN","type":"education","lineage":["https://openalex.org/I3131625388"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junke Li","raw_affiliation_strings":["Shenzhen Key Lab of Broadband Network and Multimedia, Graduate School at Shenzhen, Tsinghua University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Shenzhen Key Lab of Broadband Network and Multimedia, Graduate School at Shenzhen, Tsinghua University, Shenzhen, China","institution_ids":["https://openalex.org/I99065089","https://openalex.org/I3131625388"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023967844","display_name":"Xin Jin","orcid":"https://orcid.org/0000-0001-6655-3888"},"institutions":[{"id":"https://openalex.org/I3131625388","display_name":"University Town of Shenzhen","ror":"https://ror.org/05f5j6225","country_code":"CN","type":"education","lineage":["https://openalex.org/I3131625388"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"funder","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Jin","raw_affiliation_strings":["Shenzhen Key Lab of Broadband Network and Multimedia, Graduate School at Shenzhen, Tsinghua University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Shenzhen Key Lab of Broadband Network and Multimedia, Graduate School at Shenzhen, Tsinghua University, Shenzhen, China","institution_ids":["https://openalex.org/I3131625388","https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013695202","display_name":"Yanqin Chen","orcid":"https://orcid.org/0000-0002-3302-7643"},"institutions":[{"id":"https://openalex.org/I3131625388","display_name":"University Town of Shenzhen","ror":"https://ror.org/05f5j6225","country_code":"CN","type":"education","lineage":["https://openalex.org/I3131625388"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"funder","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanqin Chen","raw_affiliation_strings":["Shenzhen Key Lab of Broadband Network and Multimedia, Graduate School at Shenzhen, Tsinghua University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Shenzhen Key Lab of Broadband Network and Multimedia, Graduate School at Shenzhen, Tsinghua University, Shenzhen, China","institution_ids":["https://openalex.org/I3131625388","https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080722708","display_name":"Qionghai Dai","orcid":"https://orcid.org/0000-0001-7043-3061"},"institutions":[{"id":"https://openalex.org/I3131625388","display_name":"University Town of Shenzhen","ror":"https://ror.org/05f5j6225","country_code":"CN","type":"education","lineage":["https://openalex.org/I3131625388"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"funder","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qionghai Dai","raw_affiliation_strings":["Shenzhen Key Lab of Broadband Network and Multimedia, Graduate School at Shenzhen, Tsinghua University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Shenzhen Key Lab of Broadband Network and Multimedia, Graduate School at Shenzhen, Tsinghua University, Shenzhen, China","institution_ids":["https://openalex.org/I3131625388","https://openalex.org/I99065089"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":0,"max":62},"biblio":{"volume":null,"issue":null,"first_page":"220","last_page":"225"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":1.0,"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/T10531","display_name":"Advanced Vision and Imaging","score":1.0,"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9985,"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"}},{"id":"https://openalex.org/T10638","display_name":"Optical measurement and interference techniques","score":0.9984,"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/structure-tensor","display_name":"Structure tensor","score":0.59756225},{"id":"https://openalex.org/keywords/sliding-window-protocol","display_name":"Sliding window protocol","score":0.50633967}],"concepts":[{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.6144803},{"id":"https://openalex.org/C113315163","wikidata":"https://www.wikidata.org/wiki/Q7625159","display_name":"Structure tensor","level":3,"score":0.59756225},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.51184624},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5075184},{"id":"https://openalex.org/C102392041","wikidata":"https://www.wikidata.org/wiki/Q592860","display_name":"Sliding window protocol","level":3,"score":0.50633967},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.48758},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.46822163},{"id":"https://openalex.org/C9395851","wikidata":"https://www.wikidata.org/wiki/Q177929","display_name":"Stack (abstract data type)","level":2,"score":0.42794833},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.41856623},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32510003},{"id":"https://openalex.org/C2778751112","wikidata":"https://www.wikidata.org/wiki/Q835016","display_name":"Window (computing)","level":2,"score":0.22555402},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1648322},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.09416929},{"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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/ispacs.2018.8923499","pdf_url":null,"source":{"id":"https://openalex.org/S4363605678","display_name":"2021 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_indexed_in_scopus":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":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[],"grants":[],"datasets":[],"versions":[],"referenced_works_count":15,"referenced_works":["https://openalex.org/W1585668122","https://openalex.org/W1781337833","https://openalex.org/W1914596733","https://openalex.org/W2042680715","https://openalex.org/W2128268941","https://openalex.org/W2128359381","https://openalex.org/W2129103953","https://openalex.org/W2133515844","https://openalex.org/W2137313943","https://openalex.org/W2149694199","https://openalex.org/W2159722793","https://openalex.org/W2200825767","https://openalex.org/W2289524987","https://openalex.org/W2346725554","https://openalex.org/W2753230437"],"related_works":["https://openalex.org/W89301254","https://openalex.org/W4400976415","https://openalex.org/W3206725971","https://openalex.org/W3174244707","https://openalex.org/W2944675036","https://openalex.org/W2770255720","https://openalex.org/W2623954137","https://openalex.org/W2535084101","https://openalex.org/W2015754241","https://openalex.org/W1974463337"],"abstract_inverted_index":{"Recently,":[0],"several":[1],"depth":[2,27,43,84,97,105,129],"estimation":[3,28],"methods":[4],"have":[5],"been":[6],"proposed":[7,31,56,122],"for":[8,75],"light":[9],"field":[10],"cameras.":[11],"However,":[12],"their":[13],"performance":[14],"is":[15,30,55,73,86,107],"limited":[16],"to":[17,32,57,64],"the":[18,36,42,47,60,65,69,89,92,96,100,103,121],"scenes":[19],"with":[20],"occlusions.":[21],"In":[22],"this":[23],"paper,":[24],"an":[25],"enhanced":[26],"method":[29,123],"improve":[33],"accuracy":[34,130],"in":[35,68,79,127],"occluded":[37],"regions.":[38],"Instead":[39],"of":[40,91],"extracting":[41],"tensor":[44,53,62,85,98],"directly":[45],"from":[46],"whole":[48],"angular":[49,70,93],"patch,":[50],"a":[51,80,113],"variable-patch-size":[52],"extraction":[54],"find":[58],"out":[59],"optimal":[61,83],"adapting":[63],"occlusion":[66],"feature":[67],"patch.":[71,94],"Variance":[72],"calculated":[74],"each":[76],"subangular":[77],"patch":[78],"sliding-window-manner.":[81],"The":[82],"determined":[87],"by":[88,112],"entropy":[90],"Minimizing":[95],"along":[99],"focal":[101],"stack,":[102],"initial":[104],"map":[106],"generated":[108],"and":[109,131],"further":[110],"optimized":[111],"multi-label":[114],"fusion":[115],"model.":[116],"Experimental":[117],"results":[118],"demonstrate":[119],"that":[120],"outperforms":[124],"state-of-the-art":[125],"approaches":[126],"higher":[128],"much":[132],"lower":[133],"computational":[134],"complexity.":[135]},"abstract_inverted_index_v3":null,"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W2993559917","counts_by_year":[],"updated_date":"2025-01-26T05:54:32.814645","created_date":"2019-12-13"}