{"id":"https://openalex.org/W3160276755","doi":"https://doi.org/10.1109/icpr48806.2021.9412007","title":"A Novel Deep-learning Pipeline for Light Field Image Based Material Recognition","display_name":"A Novel Deep-learning Pipeline for Light Field Image Based Material Recognition","publication_year":2021,"publication_date":"2021-01-10","ids":{"openalex":"https://openalex.org/W3160276755","doi":"https://doi.org/10.1109/icpr48806.2021.9412007","mag":"3160276755"},"language":"en","primary_location":{"id":"doi:10.1109/icpr48806.2021.9412007","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr48806.2021.9412007","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 25th International Conference on Pattern Recognition (ICPR)","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/A5100398969","display_name":"Yunlong Wang","orcid":"https://orcid.org/0000-0002-3535-308X"},"institutions":[{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunlong Wang","raw_affiliation_strings":["CRIPAC, NLPR, CASIA, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CRIPAC, NLPR, CASIA, Beijing, China","institution_ids":["https://openalex.org/I4210112150"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079579315","display_name":"Kunbo Zhang","orcid":"https://orcid.org/0000-0002-4826-6831"},"institutions":[{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kunbo Zhang","raw_affiliation_strings":["CRIPAC, NLPR, CASIA, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CRIPAC, NLPR, CASIA, Beijing, China","institution_ids":["https://openalex.org/I4210112150"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5055505703","display_name":"Zhenan Sun","orcid":"https://orcid.org/0000-0003-4029-9935"},"institutions":[{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenan Sun","raw_affiliation_strings":["CRIPAC, NLPR, CASIA, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CRIPAC, NLPR, CASIA, Beijing, China","institution_ids":["https://openalex.org/I4210112150"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210112150"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2422","last_page":"2429"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","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"}},"topics":[{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","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/T11019","display_name":"Image Enhancement Techniques","score":0.9972000122070312,"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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9968000054359436,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental 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":0.7702040672302246},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7653321027755737},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.6113744974136353},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5810990333557129},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5590366125106812},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.49039649963378906},{"id":"https://openalex.org/keywords/concatenation","display_name":"Concatenation (mathematics)","score":0.48743942379951477},{"id":"https://openalex.org/keywords/light-field","display_name":"Light field","score":0.481767863035202},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.47627371549606323},{"id":"https://openalex.org/keywords/cognitive-neuroscience-of-visual-object-recognition","display_name":"Cognitive neuroscience of visual object recognition","score":0.4497593641281128},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.43613603711128235},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.427166610956192},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.42639297246932983},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.41646984219551086},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07785174250602722}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7702040672302246},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7653321027755737},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.6113744974136353},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5810990333557129},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5590366125106812},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.49039649963378906},{"id":"https://openalex.org/C87619178","wikidata":"https://www.wikidata.org/wiki/Q126002","display_name":"Concatenation (mathematics)","level":2,"score":0.48743942379951477},{"id":"https://openalex.org/C48983235","wikidata":"https://www.wikidata.org/wiki/Q593161","display_name":"Light field","level":2,"score":0.481767863035202},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.47627371549606323},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.4497593641281128},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.43613603711128235},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.427166610956192},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.42639297246932983},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.41646984219551086},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07785174250602722},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","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/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icpr48806.2021.9412007","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr48806.2021.9412007","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 25th International Conference on Pattern Recognition (ICPR)","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":41,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1533861849","https://openalex.org/W1909952827","https://openalex.org/W1933349210","https://openalex.org/W1948912989","https://openalex.org/W1953465585","https://openalex.org/W1954665043","https://openalex.org/W2000123870","https://openalex.org/W2007512851","https://openalex.org/W2053544201","https://openalex.org/W2059552065","https://openalex.org/W2064675550","https://openalex.org/W2071527584","https://openalex.org/W2075019799","https://openalex.org/W2115613106","https://openalex.org/W2128268941","https://openalex.org/W2137313943","https://openalex.org/W2153786187","https://openalex.org/W2239879258","https://openalex.org/W2464308330","https://openalex.org/W2513285095","https://openalex.org/W2551052086","https://openalex.org/W2588196171","https://openalex.org/W2612981966","https://openalex.org/W2716916105","https://openalex.org/W2744570394","https://openalex.org/W2800554784","https://openalex.org/W2895527865","https://openalex.org/W2897594148","https://openalex.org/W2903622424","https://openalex.org/W2914600502","https://openalex.org/W2947690922","https://openalex.org/W2963872754","https://openalex.org/W2964121744","https://openalex.org/W2964178790","https://openalex.org/W2971652148","https://openalex.org/W3016705580","https://openalex.org/W6631943919","https://openalex.org/W6680152570","https://openalex.org/W6725968855","https://openalex.org/W6737950358"],"related_works":["https://openalex.org/W2373577936","https://openalex.org/W4221148444","https://openalex.org/W4387678054","https://openalex.org/W2389596151","https://openalex.org/W3095575180","https://openalex.org/W4306784355","https://openalex.org/W2169308097","https://openalex.org/W2784004155","https://openalex.org/W3091984855","https://openalex.org/W2150768546"],"abstract_inverted_index":{"The":[0],"primitive":[1],"basis":[2],"of":[3,17,64,93,160],"image":[4,67],"based":[5,68],"material":[6,48,69,137,162,166],"recognition":[7,138],"builds":[8],"upon":[9,114],"the":[10,15,120,150,170],"fact":[11],"that":[12,149],"discrepancies":[13],"in":[14],"reflectances":[16],"distinct":[18],"materials":[19],"lead":[20],"to":[21,32,61,88,100,118,190],"imaging":[22,121],"differences":[23],"under":[24],"multiple":[25,34],"viewpoints.":[26],"LF":[27,184],"cameras":[28],"possess":[29],"coherent":[30],"abilities":[31],"capture":[33],"sub-aperture":[35],"views":[36],"(SAIs)":[37],"within":[38],"one":[39],"exposure,":[40],"which":[41],"can":[42,139,153,173],"provide":[43],"appropriate":[44],"multi-view":[45],"sources":[46],"for":[47,136,195],"recognition.":[49,70],"In":[50,168],"this":[51],"paper,":[52],"a":[53],"unified":[54],"\u201cFactorize-Connect-Merge\u201d":[55],"(FCM)":[56],"deep-learning":[57],"pipeline":[58,152,172],"is":[59,76,86,112],"proposed":[60,151,171],"solve":[62],"problems":[63],"light":[65],"field":[66],"4D":[71,143,192],"light-field":[72,82,144,193],"data":[73],"as":[74,186,200],"input":[75,187],"initially":[77],"decomposed":[78],"into":[79],"consecutive":[80],"3D":[81],"slices.":[83,98],"Shallow":[84],"CNN":[85],"leveraged":[87],"extract":[89,191],"low-level":[90,116],"visual":[91],"features":[92,117],"each":[94],"view":[95],"inside":[96],"these":[97,104,115],"As":[99],"establish":[101],"correspondences":[102],"between":[103],"SAIs,":[105],"Bidirectional":[106],"Long-Short":[107],"Term":[108],"Memory":[109],"(Bi-LSTM)":[110],"network":[111],"built":[113],"model":[119],"differences.":[122],"After":[123],"feature":[124,134],"selection":[125],"including":[126],"concatenation":[127],"and":[128,132,164,176,188,205],"dimension":[129],"reduction,":[130],"effective":[131],"robust":[133],"representations":[135,194],"be":[140],"extracted":[141],"from":[142],"data.":[145],"Experimental":[146],"results":[147],"indicate":[148],"obtain":[154],"remarkable":[155],"performances":[156],"on":[157],"both":[158],"tasks":[159,198],"single-pixel":[161],"classification":[163],"full-image":[165],"segmentation.":[167],"addition,":[169],"potentially":[174],"benefit":[175],"inspire":[177],"other":[178],"researchers":[179],"who":[180],"may":[181],"also":[182],"take":[183],"images":[185],"need":[189],"computer":[196],"vision":[197],"such":[199],"object":[201],"classification,":[202],"semantic":[203],"segmentation":[204],"edge":[206],"detection.":[207]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}