{"id":"https://openalex.org/W2343797416","doi":"https://doi.org/10.1117/12.2227797","title":"Real-time framework for tensor-based image enhancement for object classification","display_name":"Real-time framework for tensor-based image enhancement for object classification","publication_year":2016,"publication_date":"2016-04-29","ids":{"openalex":"https://openalex.org/W2343797416","doi":"https://doi.org/10.1117/12.2227797","mag":"2343797416"},"language":"en","primary_location":{"id":"doi:10.1117/12.2227797","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2227797","pdf_url":null,"source":{"id":"https://openalex.org/S183492911","display_name":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","issn_l":"0277-786X","issn":["0277-786X","1996-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315543","host_organization_name":"SPIE","host_organization_lineage":["https://openalex.org/P4310315543"],"host_organization_lineage_names":["SPIE"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SPIE Proceedings","raw_type":"proceedings-article"},"type":"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/A5084051053","display_name":"Bogus\u0142aw Cyganek","orcid":"https://orcid.org/0000-0001-5185-1145"},"institutions":[{"id":"https://openalex.org/I686019","display_name":"AGH University of Krakow","ror":"https://ror.org/00bas1c41","country_code":"PL","type":"education","lineage":["https://openalex.org/I686019"]}],"countries":["PL"],"is_corresponding":true,"raw_author_name":"Bogus\u0142aw Cyganek","raw_affiliation_strings":["AGH Univ. of Science and Technology (Poland)"],"affiliations":[{"raw_affiliation_string":"AGH Univ. of Science and Technology (Poland)","institution_ids":["https://openalex.org/I686019"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064459980","display_name":"Bogdan Smo\u0142ka","orcid":"https://orcid.org/0000-0003-1883-3580"},"institutions":[{"id":"https://openalex.org/I119004910","display_name":"Silesian University of Technology","ror":"https://ror.org/02dyjk442","country_code":"PL","type":"education","lineage":["https://openalex.org/I119004910"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Bogdan Smo\u0142ka","raw_affiliation_strings":["Silesian Univ. of Technology (Poland)"],"affiliations":[{"raw_affiliation_string":"Silesian Univ. of Technology (Poland)","institution_ids":["https://openalex.org/I119004910"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5084051053"],"corresponding_institution_ids":["https://openalex.org/I686019"],"apc_list":null,"apc_paid":null,"fwci":0.2935,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.47409733,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":"9897","issue":null,"first_page":"98970Q","last_page":"98970Q"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12303","display_name":"Tensor decomposition and applications","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2605","display_name":"Computational Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12303","display_name":"Tensor decomposition and applications","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2605","display_name":"Computational Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9671000242233276,"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/T11269","display_name":"Algorithms and Data Compression","score":0.9519000053405762,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7150106430053711},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6754895448684692},{"id":"https://openalex.org/keywords/tensor","display_name":"Tensor (intrinsic definition)","score":0.6566365361213684},{"id":"https://openalex.org/keywords/tucker-decomposition","display_name":"Tucker decomposition","score":0.6187151670455933},{"id":"https://openalex.org/keywords/singular-value-decomposition","display_name":"Singular value decomposition","score":0.6008079051971436},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5952669382095337},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5187128186225891},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5179311633110046},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.5118807554244995},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.49939680099487305},{"id":"https://openalex.org/keywords/multilinear-map","display_name":"Multilinear map","score":0.4854500889778137},{"id":"https://openalex.org/keywords/projection","display_name":"Projection (relational algebra)","score":0.43900996446609497},{"id":"https://openalex.org/keywords/cognitive-neuroscience-of-visual-object-recognition","display_name":"Cognitive neuroscience of visual object recognition","score":0.4136376678943634},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2829161286354065},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2440062165260315},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.20119652152061462},{"id":"https://openalex.org/keywords/tensor-decomposition","display_name":"Tensor decomposition","score":0.12496623396873474}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7150106430053711},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6754895448684692},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.6566365361213684},{"id":"https://openalex.org/C42704193","wikidata":"https://www.wikidata.org/wiki/Q7851097","display_name":"Tucker decomposition","level":4,"score":0.6187151670455933},{"id":"https://openalex.org/C22789450","wikidata":"https://www.wikidata.org/wiki/Q420904","display_name":"Singular value decomposition","level":2,"score":0.6008079051971436},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5952669382095337},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5187128186225891},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5179311633110046},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.5118807554244995},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.49939680099487305},{"id":"https://openalex.org/C84392682","wikidata":"https://www.wikidata.org/wiki/Q1952404","display_name":"Multilinear map","level":2,"score":0.4854500889778137},{"id":"https://openalex.org/C57493831","wikidata":"https://www.wikidata.org/wiki/Q3134666","display_name":"Projection (relational algebra)","level":2,"score":0.43900996446609497},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.4136376678943634},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2829161286354065},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2440062165260315},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.20119652152061462},{"id":"https://openalex.org/C2986737658","wikidata":"https://www.wikidata.org/wiki/Q30103009","display_name":"Tensor decomposition","level":3,"score":0.12496623396873474},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1117/12.2227797","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2227797","pdf_url":null,"source":{"id":"https://openalex.org/S183492911","display_name":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","issn_l":"0277-786X","issn":["0277-786X","1996-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315543","host_organization_name":"SPIE","host_organization_lineage":["https://openalex.org/P4310315543"],"host_organization_lineage_names":["SPIE"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SPIE Proceedings","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/1","score":0.47999998927116394,"display_name":"No poverty"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W32702425","https://openalex.org/W371810238","https://openalex.org/W1535749512","https://openalex.org/W1971153605","https://openalex.org/W1972226726","https://openalex.org/W1974388905","https://openalex.org/W2013912476","https://openalex.org/W2019502123","https://openalex.org/W2024165284","https://openalex.org/W2036226226","https://openalex.org/W2038705219","https://openalex.org/W2060225944","https://openalex.org/W2077099873","https://openalex.org/W2086022711","https://openalex.org/W2096710051","https://openalex.org/W2100659887","https://openalex.org/W2112796928","https://openalex.org/W2497539787","https://openalex.org/W4248056595","https://openalex.org/W4301621763"],"related_works":["https://openalex.org/W2535617683","https://openalex.org/W3202440455","https://openalex.org/W2038198231","https://openalex.org/W4284965568","https://openalex.org/W3203680175","https://openalex.org/W4320519572","https://openalex.org/W4226317016","https://openalex.org/W2922481674","https://openalex.org/W4251688473","https://openalex.org/W2464767573"],"abstract_inverted_index":{"In":[0,74,142],"many":[1],"practical":[2,200],"situations":[3],"visual":[4],"pattern":[5],"recognition":[6,66,154],"is":[7,95,120],"vastly":[8],"burdened":[9],"by":[10,97,108,122],"low":[11,24],"quality":[12,25,37,163],"of":[13,26,35,124,174,176,189,205,209],"input":[14,100],"images":[15,182],"due":[16],"to":[17,54,138,203],"noise,":[18],"geometrical":[19],"distortions,":[20],"as":[21,23,40,68,180],"well":[22],"the":[27,50,89,98,104,109,115,125,131,139,143,148,157,161,168,206,210],"acquisition":[28],"hardware.":[29],"However,":[30],"although":[31],"there":[32,43],"are":[33,44,187],"techniques":[34],"image":[36],"improvements,":[38],"such":[39,67,179],"nonlinear":[41],"filtering,":[42],"only":[45],"few":[46],"attempts":[47],"reported":[48],"in":[49,156],"literature":[51],"that":[52,147],"try":[53],"build":[55],"these":[56],"enhancement":[57],"methods":[58],"into":[59,103],"a":[60,79],"complete":[61],"chain":[62,150],"for":[63],"multi-dimensional":[64,90,99],"object":[65,118,153],"color":[69,181],"video":[70,184],"or":[71,183],"hyperspectral":[72],"images.":[73],"this":[75],"work":[76],"we":[77,145],"propose":[78],"joint":[80],"multilinear":[81],"signal":[82,101],"filtering":[83,94],"and":[84,191],"classification":[85,119,173],"system":[86],"built":[87],"upon":[88],"(tensor)":[91],"approach.":[92],"Tensor":[93],"performed":[96],"projection":[102],"tensor":[105,111,126],"subspace":[106],"spanned":[107],"best-rank":[110],"decomposition":[112],"method.":[113],"On":[114],"other":[116],"hand,":[117],"done":[121],"construction":[123],"sub-space":[127],"constructed":[128],"based":[129],"on":[130],"Higher-Order":[132],"Singular":[133],"Value":[134],"Decomposition":[135],"method":[136],"applied":[137],"prototype":[140],"patters.":[141],"experiments":[144],"show":[146],"proposed":[149,169,211],"allows":[151,171],"high":[152],"accuracy":[155],"real-time":[158],"even":[159],"from":[160],"poor":[162],"prototypes.":[164],"Even":[165],"more":[166],"importantly,":[167],"framework":[170],"unified":[172],"signals":[175],"any":[177],"dimensions,":[178],"sequences":[185],"which":[186],"exemplars":[188],"3D":[190],"4D":[192],"tensors,":[193],"respectively.":[194],"The":[195],"paper":[196],"discussed":[197],"also":[198],"some":[199],"issues":[201],"related":[202],"implementation":[204],"key":[207],"components":[208],"system.":[212]},"counts_by_year":[{"year":2021,"cited_by_count":2},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
