{"id":"https://openalex.org/W2567682896","doi":"https://doi.org/10.1109/dicta.2016.7797085","title":"Sparse Wavelet Auto-Encoders for Image Classification","display_name":"Sparse Wavelet Auto-Encoders for Image Classification","publication_year":2016,"publication_date":"2016-11-01","ids":{"openalex":"https://openalex.org/W2567682896","doi":"https://doi.org/10.1109/dicta.2016.7797085","mag":"2567682896"},"language":"en","primary_location":{"id":"doi:10.1109/dicta.2016.7797085","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dicta.2016.7797085","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 International Conference on Digital Image Computing: Techniques and Applications (DICTA)","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/A5072837793","display_name":"Salima Hassairi","orcid":"https://orcid.org/0000-0003-3281-6576"},"institutions":[{"id":"https://openalex.org/I142899784","display_name":"University of Sfax","ror":"https://ror.org/04d4sd432","country_code":"TN","type":"education","lineage":["https://openalex.org/I142899784"]}],"countries":["TN"],"is_corresponding":false,"raw_author_name":"Salima Hassairi","raw_affiliation_strings":["REGIM-Lab: REsearch Groups in Intelligent Machines, National Engineering School of Sfax (ENIS), Sfax, Tunisia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"REGIM-Lab: REsearch Groups in Intelligent Machines, National Engineering School of Sfax (ENIS), Sfax, Tunisia","institution_ids":["https://openalex.org/I142899784"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029856197","display_name":"Ridha Ejbali","orcid":"https://orcid.org/0000-0002-8148-1621"},"institutions":[{"id":"https://openalex.org/I142899784","display_name":"University of Sfax","ror":"https://ror.org/04d4sd432","country_code":"TN","type":"education","lineage":["https://openalex.org/I142899784"]}],"countries":["TN"],"is_corresponding":false,"raw_author_name":"Ridha Ejbali","raw_affiliation_strings":["REGIM-Lab: REsearch Groups in Intelligent Machines, National Engineering School of Sfax (ENIS), Sfax, Tunisia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"REGIM-Lab: REsearch Groups in Intelligent Machines, National Engineering School of Sfax (ENIS), Sfax, Tunisia","institution_ids":["https://openalex.org/I142899784"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074838703","display_name":"Mourad Zaied","orcid":"https://orcid.org/0000-0003-4013-5834"},"institutions":[{"id":"https://openalex.org/I142899784","display_name":"University of Sfax","ror":"https://ror.org/04d4sd432","country_code":"TN","type":"education","lineage":["https://openalex.org/I142899784"]}],"countries":["TN"],"is_corresponding":false,"raw_author_name":"Mourad Zaied","raw_affiliation_strings":["REGIM-Lab: REsearch Groups in Intelligent Machines, National Engineering School of Sfax (ENIS), Sfax, Tunisia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"REGIM-Lab: REsearch Groups in Intelligent Machines, National Engineering School of Sfax (ENIS), Sfax, Tunisia","institution_ids":["https://openalex.org/I142899784"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.507,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.74516193,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"31","issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9994999766349792,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9994999766349792,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9987999796867371,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9983000159263611,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7804642915725708},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.728927731513977},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7108235955238342},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.6377158164978027},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.5669628381729126},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.5602049231529236},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.522068202495575},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5169340968132019},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.49930739402770996},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.48984047770500183},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4634871780872345},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3415600061416626}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7804642915725708},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.728927731513977},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7108235955238342},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.6377158164978027},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.5669628381729126},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.5602049231529236},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.522068202495575},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5169340968132019},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.49930739402770996},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.48984047770500183},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4634871780872345},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3415600061416626},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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":2,"locations":[{"id":"doi:10.1109/dicta.2016.7797085","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dicta.2016.7797085","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 International Conference on Digital Image Computing: Techniques and Applications (DICTA)","raw_type":"proceedings-article"},{"id":"mag:2745817085","is_oa":false,"landing_page_url":"http://jglobal.jst.go.jp/en/public/20090422/201702252079572910","pdf_url":null,"source":{"id":"https://openalex.org/S4306512817","display_name":"IEEE Conference Proceedings","issn_l":null,"issn":null,"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":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":"IEEE Conference Proceedings","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W104211377","https://openalex.org/W191001584","https://openalex.org/W649855407","https://openalex.org/W1686810756","https://openalex.org/W1967282395","https://openalex.org/W1973279663","https://openalex.org/W2026942141","https://openalex.org/W2036109700","https://openalex.org/W2053757129","https://openalex.org/W2072128103","https://openalex.org/W2105464873","https://openalex.org/W2113606819","https://openalex.org/W2150341604","https://openalex.org/W2158978266","https://openalex.org/W2160380264","https://openalex.org/W2163605009","https://openalex.org/W2171506994","https://openalex.org/W2184852195","https://openalex.org/W2218318129","https://openalex.org/W2247478801","https://openalex.org/W2293747114","https://openalex.org/W2443439949","https://openalex.org/W4205947740","https://openalex.org/W4231109964","https://openalex.org/W6604310120","https://openalex.org/W6621527213","https://openalex.org/W6637373629","https://openalex.org/W6659357316","https://openalex.org/W6676903177","https://openalex.org/W6684191040","https://openalex.org/W6686418764","https://openalex.org/W6688386640"],"related_works":["https://openalex.org/W3013693939","https://openalex.org/W2159052453","https://openalex.org/W2566616303","https://openalex.org/W3131327266","https://openalex.org/W2734887215","https://openalex.org/W4297051394","https://openalex.org/W2752972570","https://openalex.org/W4386815338","https://openalex.org/W2077021924","https://openalex.org/W2565656575"],"abstract_inverted_index":{"The":[0,23,54,107],"goal":[1],"of":[2,20,26,50,62,78,125,132,143],"the":[3,21,60,63,73,81,85,94,96,101,112,123,126,130,138],"Deep":[4,70],"learning":[5,8],"methods":[6,66],"is":[7,29,47,56],"feature":[9],"hierarchies":[10],"with":[11],"features":[12,19,35],"from":[13],"higher":[14],"levels":[15],"to":[16,30,33,150],"lower":[17],"level":[18],"hierarchy.":[22],"major":[24],"contribution":[25],"this":[27],"paper":[28],"show":[31],"how":[32],"extract":[34],"and":[36,72,84,100,129],"train":[37],"an":[38,48],"image":[39,68,147],"classification":[40,148],"system":[41],"on":[42],"large-scale":[43],"datasets.":[44],"This":[45],"method":[46],"improvement":[49],"our":[51,91,144],"recent":[52],"work.":[53],"training":[55,139],"carried":[57],"out":[58],"by":[59],"combination":[61],"most":[64],"used":[65,89,110,118],"for":[67,137,146],"classification:":[69],"Learning":[71],"Wavelet":[74,98],"Network.":[75],"Some":[76],"algorithms":[77],"DL":[79],"like":[80],"sparse":[82],"coding":[83],"stacked":[86],"autoencoders":[87],"are":[88,105],"in":[90,111,115],"approach.":[92,152],"For":[93],"WN,":[95],"Fast":[97],"Transform":[99],"Best":[102],"Contribution":[103],"Algorithm":[104],"utilized.":[106],"ImageNet":[108],"dataset":[109],"test":[113],"phase":[114],"which":[116],"we":[117,135],"many":[119],"criteria":[120],"such":[121],"as":[122],"number":[124,131],"hidden":[127],"layers":[128],"images":[133],"that":[134],"specified":[136],"shows":[140],"great":[141],"efficiency":[142],"model":[145],"compared":[149],"another":[151]},"counts_by_year":[{"year":2022,"cited_by_count":2},{"year":2018,"cited_by_count":3}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
