{"id":"https://openalex.org/W3114207337","doi":"https://doi.org/10.1109/mmsp48831.2020.9287107","title":"Convolution Autoencoder-Based Sparse Representation Wavelet for Image Classification","display_name":"Convolution Autoencoder-Based Sparse Representation Wavelet for Image Classification","publication_year":2020,"publication_date":"2020-09-21","ids":{"openalex":"https://openalex.org/W3114207337","doi":"https://doi.org/10.1109/mmsp48831.2020.9287107","mag":"3114207337"},"language":"en","primary_location":{"id":"doi:10.1109/mmsp48831.2020.9287107","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mmsp48831.2020.9287107","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE 22nd International Workshop on Multimedia Signal Processing (MMSP)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://hal.science/hal-04453694","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5048006732","display_name":"Tan-Sy Nguyen","orcid":"https://orcid.org/0000-0003-2475-8177"},"institutions":[{"id":"https://openalex.org/I39804081","display_name":"Sorbonne Universit\u00e9","ror":"https://ror.org/02en5vm52","country_code":"FR","type":"education","lineage":["https://openalex.org/I39804081"]},{"id":"https://openalex.org/I4210091279","display_name":"Universit\u00e9 Sorbonne Paris Nord","ror":"https://ror.org/0199hds37","country_code":"FR","type":"education","lineage":["https://openalex.org/I4210091279"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Tan-Sy Nguyen","raw_affiliation_strings":["Universit\u00e9 Sorbonne Paris Nord, France","L2TI - Laboratoire de Traitement et Transport de l'Information (Institut Galil\u00e9e, Universit\u00e9 Paris 13, 99 avenue Jean-Baptiste Cl\u00e9ment, F-93430, Villetaneuse - France)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universit\u00e9 Sorbonne Paris Nord, France","institution_ids":["https://openalex.org/I39804081","https://openalex.org/I4210091279"]},{"raw_affiliation_string":"L2TI - Laboratoire de Traitement et Transport de l'Information (Institut Galil\u00e9e, Universit\u00e9 Paris 13, 99 avenue Jean-Baptiste Cl\u00e9ment, F-93430, Villetaneuse - France)","institution_ids":["https://openalex.org/I4210091279"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005898239","display_name":"Long H. Ngo","orcid":"https://orcid.org/0000-0003-1497-3981"},"institutions":[{"id":"https://openalex.org/I39804081","display_name":"Sorbonne Universit\u00e9","ror":"https://ror.org/02en5vm52","country_code":"FR","type":"education","lineage":["https://openalex.org/I39804081"]},{"id":"https://openalex.org/I4210091279","display_name":"Universit\u00e9 Sorbonne Paris Nord","ror":"https://ror.org/0199hds37","country_code":"FR","type":"education","lineage":["https://openalex.org/I4210091279"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Long H. Ngo","raw_affiliation_strings":["Universit\u00e9 Sorbonne Paris Nord, France","L2TI - Laboratoire de Traitement et Transport de l'Information (Institut Galil\u00e9e, Universit\u00e9 Paris 13, 99 avenue Jean-Baptiste Cl\u00e9ment, F-93430, Villetaneuse - France)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universit\u00e9 Sorbonne Paris Nord, France","institution_ids":["https://openalex.org/I39804081","https://openalex.org/I4210091279"]},{"raw_affiliation_string":"L2TI - Laboratoire de Traitement et Transport de l'Information (Institut Galil\u00e9e, Universit\u00e9 Paris 13, 99 avenue Jean-Baptiste Cl\u00e9ment, F-93430, Villetaneuse - France)","institution_ids":["https://openalex.org/I4210091279"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113726809","display_name":"Marie Luong","orcid":null},"institutions":[{"id":"https://openalex.org/I39804081","display_name":"Sorbonne Universit\u00e9","ror":"https://ror.org/02en5vm52","country_code":"FR","type":"education","lineage":["https://openalex.org/I39804081"]},{"id":"https://openalex.org/I4210091279","display_name":"Universit\u00e9 Sorbonne Paris Nord","ror":"https://ror.org/0199hds37","country_code":"FR","type":"education","lineage":["https://openalex.org/I4210091279"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Marie Luong","raw_affiliation_strings":["Universit\u00e9 Sorbonne Paris Nord, France","L2TI - Laboratoire de Traitement et Transport de l'Information (Institut Galil\u00e9e, Universit\u00e9 Paris 13, 99 avenue Jean-Baptiste Cl\u00e9ment, F-93430, Villetaneuse - France)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universit\u00e9 Sorbonne Paris Nord, France","institution_ids":["https://openalex.org/I39804081","https://openalex.org/I4210091279"]},{"raw_affiliation_string":"L2TI - Laboratoire de Traitement et Transport de l'Information (Institut Galil\u00e9e, Universit\u00e9 Paris 13, 99 avenue Jean-Baptiste Cl\u00e9ment, F-93430, Villetaneuse - France)","institution_ids":["https://openalex.org/I4210091279"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051468325","display_name":"Mounir Kaaniche","orcid":"https://orcid.org/0000-0003-1874-3243"},"institutions":[{"id":"https://openalex.org/I39804081","display_name":"Sorbonne Universit\u00e9","ror":"https://ror.org/02en5vm52","country_code":"FR","type":"education","lineage":["https://openalex.org/I39804081"]},{"id":"https://openalex.org/I4210091279","display_name":"Universit\u00e9 Sorbonne Paris Nord","ror":"https://ror.org/0199hds37","country_code":"FR","type":"education","lineage":["https://openalex.org/I4210091279"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Mounir Kaaniche","raw_affiliation_strings":["Universit\u00e9 Sorbonne Paris Nord, France","L2TI - Laboratoire de Traitement et Transport de l'Information (Institut Galil\u00e9e, Universit\u00e9 Paris 13, 99 avenue Jean-Baptiste Cl\u00e9ment, F-93430, Villetaneuse - France)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universit\u00e9 Sorbonne Paris Nord, France","institution_ids":["https://openalex.org/I39804081","https://openalex.org/I4210091279"]},{"raw_affiliation_string":"L2TI - Laboratoire de Traitement et Transport de l'Information (Institut Galil\u00e9e, Universit\u00e9 Paris 13, 99 avenue Jean-Baptiste Cl\u00e9ment, F-93430, Villetaneuse - France)","institution_ids":["https://openalex.org/I4210091279"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010658612","display_name":"Azeddine Beghdadi","orcid":"https://orcid.org/0000-0002-5595-0615"},"institutions":[{"id":"https://openalex.org/I39804081","display_name":"Sorbonne Universit\u00e9","ror":"https://ror.org/02en5vm52","country_code":"FR","type":"education","lineage":["https://openalex.org/I39804081"]},{"id":"https://openalex.org/I4210091279","display_name":"Universit\u00e9 Sorbonne Paris Nord","ror":"https://ror.org/0199hds37","country_code":"FR","type":"education","lineage":["https://openalex.org/I4210091279"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Azeddine Beghdadi","raw_affiliation_strings":["Universit\u00e9 Sorbonne Paris Nord, France","L2TI - Laboratoire de Traitement et Transport de l'Information (Institut Galil\u00e9e, Universit\u00e9 Paris 13, 99 avenue Jean-Baptiste Cl\u00e9ment, F-93430, Villetaneuse - France)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universit\u00e9 Sorbonne Paris Nord, France","institution_ids":["https://openalex.org/I39804081","https://openalex.org/I4210091279"]},{"raw_affiliation_string":"L2TI - Laboratoire de Traitement et Transport de l'Information (Institut Galil\u00e9e, Universit\u00e9 Paris 13, 99 avenue Jean-Baptiste Cl\u00e9ment, F-93430, Villetaneuse - France)","institution_ids":["https://openalex.org/I4210091279"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.5416,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.74873587,"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":"1","last_page":"6"},"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":0.9993000030517578,"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":0.9993000030517578,"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":0.9991000294685364,"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":0.9990000128746033,"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/autoencoder","display_name":"Autoencoder","score":0.9031476974487305},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7563793659210205},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.7489475607872009},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6532089710235596},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.6414668560028076},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6360787153244019},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.6156237125396729},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.5282755494117737},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4705484211444855},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.44375884532928467},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.41634514927864075},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.2373473048210144},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.16046953201293945}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.9031476974487305},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7563793659210205},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.7489475607872009},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6532089710235596},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.6414668560028076},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6360787153244019},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.6156237125396729},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.5282755494117737},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4705484211444855},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.44375884532928467},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.41634514927864075},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2373473048210144},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.16046953201293945}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/mmsp48831.2020.9287107","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mmsp48831.2020.9287107","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE 22nd International Workshop on Multimedia Signal Processing (MMSP)","raw_type":"proceedings-article"},{"id":"pmh:oai:HAL:hal-03957673v1","is_oa":false,"landing_page_url":"https://hal.science/hal-03957673","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2020 IEEE 22nd International Workshop on Multimedia Signal Processing (MMSP), Sep 2020, Tampere, Finland. pp.1-6, &#x27E8;10.1109/MMSP48831.2020.9287107&#x27E9;","raw_type":"Conference papers"},{"id":"pmh:oai:HAL:hal-04453694v1","is_oa":true,"landing_page_url":"https://hal.science/hal-04453694","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2020 IEEE 22nd International Workshop on Multimedia Signal Processing (MMSP), Sep 2020, Tampere, France. pp.1-6, &#x27E8;10.1109/MMSP48831.2020.9287107&#x27E9;","raw_type":"Conference papers"}],"best_oa_location":{"id":"pmh:oai:HAL:hal-04453694v1","is_oa":true,"landing_page_url":"https://hal.science/hal-04453694","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2020 IEEE 22nd International Workshop on Multimedia Signal Processing (MMSP), Sep 2020, Tampere, France. pp.1-6, &#x27E8;10.1109/MMSP48831.2020.9287107&#x27E9;","raw_type":"Conference papers"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W191001584","https://openalex.org/W1537211966","https://openalex.org/W1591116419","https://openalex.org/W1686810756","https://openalex.org/W1963932623","https://openalex.org/W1983864612","https://openalex.org/W2093323596","https://openalex.org/W2100659887","https://openalex.org/W2123921160","https://openalex.org/W2129812935","https://openalex.org/W2145889472","https://openalex.org/W2157785665","https://openalex.org/W2183341477","https://openalex.org/W2194775991","https://openalex.org/W2335728318","https://openalex.org/W2401231614","https://openalex.org/W2577608787","https://openalex.org/W2803775887","https://openalex.org/W2890233668","https://openalex.org/W2940990667","https://openalex.org/W2962835968","https://openalex.org/W2963197835","https://openalex.org/W2964137095","https://openalex.org/W2994340921","https://openalex.org/W3012496351","https://openalex.org/W3089412920","https://openalex.org/W3101882409","https://openalex.org/W3106375245","https://openalex.org/W4206314950","https://openalex.org/W4235713725","https://openalex.org/W4322615131","https://openalex.org/W6635552349","https://openalex.org/W6637373629","https://openalex.org/W6703116779","https://openalex.org/W6713132643","https://openalex.org/W6724411756"],"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/W2145836866","https://openalex.org/W2803255133"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3],"propose":[4],"an":[5,26],"effective":[6],"Convolutional":[7],"Autoencoder":[8],"(AE)":[9],"model":[10],"for":[11,19,33,46],"Sparse":[12],"Representation":[13],"(SR)":[14],"in":[15,78],"the":[16,66,79],"Wavelet":[17],"Domain":[18],"Classification":[20],"(SRWC).":[21],"The":[22,40],"proposed":[23,67],"approach":[24],"involves":[25],"autoencoder":[27],"with":[28],"a":[29,53,75],"sparse":[30,35,42],"latent":[31],"layer":[32],"learning":[34],"codes":[36,43],"of":[37,81],"wavelet":[38],"features.":[39],"estimated":[41],"are":[44],"used":[45],"assigning":[47],"classes":[48],"to":[49,85],"test":[50],"samples":[51],"using":[52],"residual-based":[54],"probabilistic":[55],"criterion.":[56],"Intensive":[57],"experiments":[58],"carried":[59],"out":[60],"on":[61],"various":[62],"datasets":[63],"revealed":[64],"that":[65],"method":[68],"yields":[69],"better":[70],"classification":[71],"accuracy":[72],"while":[73],"exhibiting":[74],"significant":[76],"reduction":[77],"number":[80],"network":[82],"parameters,":[83],"compared":[84],"several":[86],"recent":[87],"deep":[88],"learning-based":[89],"methods.":[90]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
