{"id":"https://openalex.org/W3201514205","doi":"https://doi.org/10.1109/ijcnn52387.2021.9533652","title":"Wavelet J-Net: A Frequency Perspective on Convolutional Neural Networks","display_name":"Wavelet J-Net: A Frequency Perspective on Convolutional Neural Networks","publication_year":2021,"publication_date":"2021-07-18","ids":{"openalex":"https://openalex.org/W3201514205","doi":"https://doi.org/10.1109/ijcnn52387.2021.9533652","mag":"3201514205"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn52387.2021.9533652","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn52387.2021.9533652","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Joint Conference on Neural Networks (IJCNN)","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/A5100689114","display_name":"Linfeng Zhang","orcid":"https://orcid.org/0000-0002-3341-183X"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Linfeng Zhang","raw_affiliation_strings":["Institute for Interdisciplinary Information Science, Tsinghua University"],"affiliations":[{"raw_affiliation_string":"Institute for Interdisciplinary Information Science, Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100605587","display_name":"Xiaoman Zhang","orcid":"https://orcid.org/0000-0002-4572-5764"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiaoman Zhang","raw_affiliation_strings":["Institute for Interdisciplinary Information Core Technology"],"affiliations":[{"raw_affiliation_string":"Institute for Interdisciplinary Information Core Technology","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054041500","display_name":"Chenglong Bao","orcid":"https://orcid.org/0000-0002-1201-1212"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenglong Bao","raw_affiliation_strings":["YAU Mathematical Sciences Center, Tsinghua University"],"affiliations":[{"raw_affiliation_string":"YAU Mathematical Sciences Center, Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006570986","display_name":"Kaisheng Ma","orcid":"https://orcid.org/0000-0001-9226-3366"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kaisheng Ma","raw_affiliation_strings":["Institute for Interdisciplinary Information Science, Tsinghua University"],"affiliations":[{"raw_affiliation_string":"Institute for Interdisciplinary Information Science, Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100689114"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":0.126,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.49571378,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9991000294685364,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9980000257492065,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.7489473223686218},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.7081819772720337},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6786433458328247},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6420886516571045},{"id":"https://openalex.org/keywords/transformation","display_name":"Transformation (genetics)","score":0.6366063952445984},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5949681997299194},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.5801989436149597},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5387127995491028},{"id":"https://openalex.org/keywords/frequency-domain","display_name":"Frequency domain","score":0.5307844877243042},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.49133530259132385},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.480003297328949},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.459564745426178},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.22987356781959534},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.18609175086021423}],"concepts":[{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.7489473223686218},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.7081819772720337},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6786433458328247},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6420886516571045},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.6366063952445984},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5949681997299194},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.5801989436149597},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5387127995491028},{"id":"https://openalex.org/C19118579","wikidata":"https://www.wikidata.org/wiki/Q786423","display_name":"Frequency domain","level":2,"score":0.5307844877243042},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.49133530259132385},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.480003297328949},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.459564745426178},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.22987356781959534},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18609175086021423},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn52387.2021.9533652","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn52387.2021.9533652","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.4699999988079071,"display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":52,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1686810756","https://openalex.org/W1839118408","https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W2108598243","https://openalex.org/W2109255472","https://openalex.org/W2115755118","https://openalex.org/W2163605009","https://openalex.org/W2166049352","https://openalex.org/W2194775991","https://openalex.org/W2382313035","https://openalex.org/W2463818697","https://openalex.org/W2549139847","https://openalex.org/W2554242204","https://openalex.org/W2560023338","https://openalex.org/W2565639579","https://openalex.org/W2613718673","https://openalex.org/W2737081839","https://openalex.org/W2752782242","https://openalex.org/W2767421475","https://openalex.org/W2776107444","https://openalex.org/W2778053709","https://openalex.org/W2786128974","https://openalex.org/W2884436604","https://openalex.org/W2914483840","https://openalex.org/W2938458886","https://openalex.org/W2946004044","https://openalex.org/W2950014519","https://openalex.org/W2951123255","https://openalex.org/W2962835968","https://openalex.org/W2963037989","https://openalex.org/W2963075964","https://openalex.org/W2963420686","https://openalex.org/W2963446712","https://openalex.org/W2963494934","https://openalex.org/W2988396473","https://openalex.org/W3007268491","https://openalex.org/W3106250896","https://openalex.org/W6620707391","https://openalex.org/W6637373629","https://openalex.org/W6638946568","https://openalex.org/W6639824700","https://openalex.org/W6684191040","https://openalex.org/W6710398183","https://openalex.org/W6719642423","https://openalex.org/W6729623471","https://openalex.org/W6745447533","https://openalex.org/W6746996375","https://openalex.org/W6748455662","https://openalex.org/W6774070773","https://openalex.org/W6785652829"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W2382174632","https://openalex.org/W2129959498","https://openalex.org/W2784060934","https://openalex.org/W2902714807","https://openalex.org/W2537489131","https://openalex.org/W2394084632","https://openalex.org/W2358293514","https://openalex.org/W3090113802","https://openalex.org/W2077021924"],"abstract_inverted_index":{"It":[0],"is":[1,101],"well":[2],"acknowledged":[3],"in":[4,90],"image":[5],"processing":[6],"domain":[7],"that":[8,58,136],"the":[9,31,37,71,81,105,123,129],"information":[10,38,124],"can":[11],"be":[12],"decomposed":[13,75],"into":[14,39,61,86],"different":[15,62,91,126],"frequency":[16,63,127],"parts":[17],"and":[18,33,65,79,111,139,147],"each":[19],"part":[20],"has":[21],"its":[22],"own":[23],"merits.":[24],"However,":[25],"existing":[26],"neural":[27,40,53,87,108,132],"networks":[28,41,54,88],"always":[29],"ignore":[30],"distinctions":[32],"straightforwardly":[34],"feed":[35],"all":[36],"together,":[42],"treating":[43],"them":[44,68],"equally.":[45],"In":[46],"this":[47],"paper,":[48],"we":[49,119],"propose":[50],"a":[51],"novel":[52],"framework":[55],"named":[56],"J-Net":[57],"decomposes":[59],"images":[60,72],"bands":[64],"then":[66,80],"processes":[67],"sequentially.":[69],"Concretely,":[70],"have":[73],"been":[74],"by":[76],"wavelet":[77,82],"transformation":[78],"coefficients":[83],"are":[84],"fed":[85],"gradually":[89],"depth":[92],"according":[93],"to":[94,103],"their":[95],"decomposition":[96],"levels.":[97],"An":[98],"attention":[99],"module":[100],"utilized":[102],"facilitate":[104],"fusion":[106],"of":[107,131],"network":[109],"features":[110],"injected":[112],"information,":[113],"yielding":[114],"significant":[115],"performance":[116],"gain.":[117],"Furthermore,":[118],"show":[120,135],"how":[121],"does":[122],"with":[125],"impact":[128],"accuracy":[130,141],"networks.":[133],"Experiments":[134],"5.91%,":[137],"5.32%":[138],"2.00%":[140],"improvements":[142],"on":[143],"Caltech":[144],"101,":[145],"Caltech256":[146],"ImageNet,":[148],"respectively.":[149]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-03-25T13:04:00.132906","created_date":"2025-10-10T00:00:00"}