{"id":"https://openalex.org/W3090942514","doi":"https://doi.org/10.1109/icip40778.2020.9191248","title":"Joint Statistical and Spatial Sparse Representation for Robust Image and Image-Set Classification","display_name":"Joint Statistical and Spatial Sparse Representation for Robust Image and Image-Set Classification","publication_year":2020,"publication_date":"2020-09-30","ids":{"openalex":"https://openalex.org/W3090942514","doi":"https://doi.org/10.1109/icip40778.2020.9191248","mag":"3090942514"},"language":"en","primary_location":{"id":"doi:10.1109/icip40778.2020.9191248","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip40778.2020.9191248","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Image Processing (ICIP)","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/A5101511712","display_name":"Hao Cheng","orcid":"https://orcid.org/0000-0003-4823-0908"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":true,"raw_author_name":"Hao Cheng","raw_affiliation_strings":["School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5024709593","display_name":"Bihan Wen","orcid":"https://orcid.org/0000-0002-6874-6453"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Bihan Wen","raw_affiliation_strings":["School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5101511712"],"corresponding_institution_ids":["https://openalex.org/I172675005"],"apc_list":null,"apc_paid":null,"fwci":0.2651,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.63612347,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"2411","last_page":"2415"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9986000061035156,"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"}},"topics":[{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9986000061035156,"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"}},{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9980000257492065,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9958000183105469,"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":0.653521716594696},{"id":"https://openalex.org/keywords/neural-coding","display_name":"Neural coding","score":0.6483230590820312},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.642704963684082},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.6260172128677368},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6173378229141235},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4740859270095825},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.46592020988464355},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.4487886130809784},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.42310672998428345},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.41279321908950806}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.653521716594696},{"id":"https://openalex.org/C77637269","wikidata":"https://www.wikidata.org/wiki/Q7002051","display_name":"Neural coding","level":2,"score":0.6483230590820312},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.642704963684082},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.6260172128677368},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6173378229141235},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4740859270095825},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.46592020988464355},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.4487886130809784},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.42310672998428345},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.41279321908950806},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip40778.2020.9191248","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip40778.2020.9191248","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Image Processing (ICIP)","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":35,"referenced_works":["https://openalex.org/W566612420","https://openalex.org/W1862697533","https://openalex.org/W1897953826","https://openalex.org/W1900408618","https://openalex.org/W1986964250","https://openalex.org/W1996939238","https://openalex.org/W2059552065","https://openalex.org/W2060994933","https://openalex.org/W2075157914","https://openalex.org/W2084146405","https://openalex.org/W2093130305","https://openalex.org/W2097018403","https://openalex.org/W2108598243","https://openalex.org/W2110599581","https://openalex.org/W2112074816","https://openalex.org/W2120453412","https://openalex.org/W2129812935","https://openalex.org/W2142040002","https://openalex.org/W2144093206","https://openalex.org/W2150600350","https://openalex.org/W2151263123","https://openalex.org/W2162813111","https://openalex.org/W2169579681","https://openalex.org/W2423822072","https://openalex.org/W2739937239","https://openalex.org/W2752965000","https://openalex.org/W2808583987","https://openalex.org/W2962905348","https://openalex.org/W2963294657","https://openalex.org/W6615889216","https://openalex.org/W6639854271","https://openalex.org/W6674642818","https://openalex.org/W6676305975","https://openalex.org/W6680889708","https://openalex.org/W6684006261"],"related_works":["https://openalex.org/W2890544631","https://openalex.org/W2067062989","https://openalex.org/W2998105788","https://openalex.org/W4205656132","https://openalex.org/W2111634407","https://openalex.org/W3004790527","https://openalex.org/W2203155458","https://openalex.org/W2783282829","https://openalex.org/W2138494306","https://openalex.org/W2539392819"],"abstract_inverted_index":{"Recent":[0],"image":[1,55,64,95,167,177],"classification":[2,58,178],"schemes,":[3],"by":[4,99,149],"learning":[5],"deep":[6,44],"features":[7],"from":[8],"large-scale":[9],"dataset,":[10],"have":[11],"achieved":[12],"the":[13,46,68,94,114,146,151,174,181],"significantly":[14],"better":[15],"results":[16],"comparing":[17],"to":[18,66,92,121,137],"classic":[19],"feature-based":[20],"approaches.":[21],"However,":[22],"there":[23],"are":[24,163],"still":[25],"challenges":[26],"in":[27],"practice,":[28],"such":[29],"as":[30,60],"classifying":[31],"noisy":[32],"image-set":[33,57,97,169],"queries":[34],"and":[35,56,70,86,106,127,153,168],"training":[36],"over":[37],"limited-scale":[38],"dataset.":[39],"Instead":[40],"of":[41,116],"applying":[42],"generic":[43],"features,":[45],"model-based":[47],"approaches":[48],"can":[49],"be":[50],"more":[51],"effective":[52],"for":[53,165],"robust":[54,166],"tasks,":[59],"we":[61,80],"need":[62],"various":[63],"priors":[65],"exploit":[67],"inter-":[69],"intra-set":[71],"data":[72],"variations":[73],"while":[74],"prevent":[75],"over-fitting.":[76],"In":[77],"this":[78],"work,":[79],"propose":[81,136],"a":[82,139],"novel":[83],"joint":[84,157],"statistical":[85],"spatial":[87],"sparse":[88,133,141],"representation,":[89],"dubbed":[90],"J3S,":[91],"model":[93],"or":[96,183],"data,":[98],"exploiting":[100],"both":[101,124],"their":[102],"local":[103,128,152],"patch":[104,129],"structures":[105,130],"global":[107,125,154],"Gaussian":[108],"distribution":[109],"into":[110],"Riemannian":[111],"manifold.":[112],"To":[113],"best":[115],"our":[117],"knowledge,":[118],"no":[119],"work":[120],"date":[122],"utilized":[123],"statistics":[126],"jointly":[131],"via":[132],"representation.":[134],"We":[135],"solve":[138],"co-regularized":[140],"coding":[142],"problem":[143],"based":[144],"on":[145],"J3S":[147,161],"model,":[148],"coupling":[150],"representations":[155],"using":[156],"sparsity.":[158],"The":[159],"learned":[160],"models":[162],"used":[164],"classification.":[170],"Experiments":[171],"show":[172],"that":[173],"proposed":[175],"J3S-based":[176],"scheme":[179],"outperforms":[180],"popular":[182],"state-of-the-art":[184],"competing":[185],"methods.":[186]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
