{"id":"https://openalex.org/W2155511299","doi":"https://doi.org/10.48550/arxiv.1505.03703","title":"A PCA-Based Convolutional Network","display_name":"A PCA-Based Convolutional Network","publication_year":2015,"publication_date":"2015-05-14","ids":{"openalex":"https://openalex.org/W2155511299","doi":"https://doi.org/10.48550/arxiv.1505.03703","mag":"2155511299"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:1505.03703","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/1505.03703","pdf_url":"https://arxiv.org/pdf/1505.03703","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1505.03703","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5058230644","display_name":"Yanhai Gan","orcid":"https://orcid.org/0000-0002-5315-2740","observed_orcids":["https://orcid.org/0000-0002-5315-2740"]},"institutions":[{"id":"https://openalex.org/I59028903","display_name":"Ocean University of China","ror":"https://ror.org/04rdtx186","country_code":"CN","type":"education","lineage":["https://openalex.org/I59028903"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gan, Yanhai","raw_affiliation_strings":["Ocean University of China Qing Dao , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ocean University of China Qing Dao , China","institution_ids":["https://openalex.org/I59028903"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100361922","display_name":"Jun Liu","orcid":"https://orcid.org/0000-0002-7280-1443","observed_orcids":["https://orcid.org/0000-0002-7280-1443"]},"institutions":[{"id":"https://openalex.org/I59028903","display_name":"Ocean University of China","ror":"https://ror.org/04rdtx186","country_code":"CN","type":"education","lineage":["https://openalex.org/I59028903"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liu, Jun","raw_affiliation_strings":["Ocean University of China Qing Dao , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ocean University of China Qing Dao , China","institution_ids":["https://openalex.org/I59028903"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029633264","display_name":"Junyu Dong","orcid":"https://orcid.org/0000-0001-7012-2087","observed_orcids":["https://orcid.org/0000-0001-7012-2087","https://orcid.org/0000-0003-1047-427X"]},"institutions":[{"id":"https://openalex.org/I59028903","display_name":"Ocean University of China","ror":"https://ror.org/04rdtx186","country_code":"CN","type":"education","lineage":["https://openalex.org/I59028903"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dong, Junyu","raw_affiliation_strings":["Ocean University of China Qing Dao , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ocean University of China Qing Dao , China","institution_ids":["https://openalex.org/I59028903"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046728432","display_name":"Guoqiang Zhong","orcid":"https://orcid.org/0000-0002-2952-6642","observed_orcids":["https://orcid.org/0000-0002-2952-6642","https://orcid.org/0000-0002-6235-933X"]},"institutions":[{"id":"https://openalex.org/I59028903","display_name":"Ocean University of China","ror":"https://ror.org/04rdtx186","country_code":"CN","type":"education","lineage":["https://openalex.org/I59028903"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhong, Guoqiang","raw_affiliation_strings":["Ocean University of China Qing Dao , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ocean University of China Qing Dao , China","institution_ids":["https://openalex.org/I59028903"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I59028903"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":23,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.7221999764442444,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.7221999764442444,"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":0.11900000274181366,"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/T10057","display_name":"Face and Expression Recognition","score":0.03700000047683716,"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/unsupervised-deep-learning","display_name":"unsupervised deep learning","score":0.9039999842643738},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"principal component analysis","score":0.8050000071525574},{"id":"https://openalex.org/keywords/convolutional-layers","display_name":"convolutional layers","score":0.5630000233650208},{"id":"https://openalex.org/keywords/feature-pooling","display_name":"feature pooling","score":0.7940000295639038},{"id":"https://openalex.org/keywords/binary-hashing","display_name":"binary hashing","score":0.9480000138282776},{"id":"https://openalex.org/keywords/filter-banks","display_name":"filter banks","score":0.5730000138282776},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"feature extraction","score":0.7450000047683716},{"id":"https://openalex.org/keywords/handwritten-digit-recognition","display_name":"handwritten digit recognition","score":0.9129999876022339},{"id":"https://openalex.org/keywords/face-recognition","display_name":"face recognition","score":1.0},{"id":"https://openalex.org/keywords/texture-classification","display_name":"texture classification","score":0.9350000023841858},{"id":"https://openalex.org/keywords/backpropagation-free-training","display_name":"backpropagation-free training","score":0.6200000047683716}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7604131698608398},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7565678358078003},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7140592336654663},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.7062163352966309},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6983057260513306},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5442367792129517},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5374200344085693},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5254154205322266},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.4449795186519623},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:1505.03703","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/1505.03703","pdf_url":"https://arxiv.org/pdf/1505.03703","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.1505.03703","doi":"https://doi.org/10.48550/arxiv.1505.03703","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1505.03703","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1505.03703","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/1505.03703","pdf_url":"https://arxiv.org/pdf/1505.03703","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"study_designs":[],"awards":[{"id":"https://openalex.org/G4074157467","display_name":null,"funder_award_id":"20120132110018","funder_id":"https://openalex.org/F4320321106","funder_display_name":"Ministry of Education of the People's Republic of China"},{"id":"https://openalex.org/G8476600357","display_name":"\u7b26\u5408\u89c6\u89c9\u611f\u77e5\u673a\u7406\u7684\u81ea\u7136\u7eb9\u7406\u751f\u6210\u6a21\u5f0f\u7814\u7a76","funder_award_id":"61271405","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321106","display_name":"Ministry of Education of the People's Republic of China","ror":"https://ror.org/01mv9t934"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2155511299.pdf","grobid_xml":"https://content.openalex.org/works/W2155511299.grobid-xml"},"referenced_works_count":16,"referenced_works":["https://openalex.org/W1616262590","https://openalex.org/W1624854622","https://openalex.org/W1904365287","https://openalex.org/W2057175746","https://openalex.org/W2105464770","https://openalex.org/W2130325614","https://openalex.org/W2135833910","https://openalex.org/W2140262144","https://openalex.org/W2141126952","https://openalex.org/W2145072179","https://openalex.org/W2147141800","https://openalex.org/W2163605009","https://openalex.org/W2167383966","https://openalex.org/W2169488311","https://openalex.org/W2188492526","https://openalex.org/W2546302380"],"related_works":["https://openalex.org/W4206786221","https://openalex.org/W2591741596","https://openalex.org/W2554117451","https://openalex.org/W1487528910","https://openalex.org/W3048718703","https://openalex.org/W1616262590","https://openalex.org/W7097605695","https://openalex.org/W2400005727","https://openalex.org/W3153573043","https://openalex.org/W2944724518"],"abstract_inverted_index":{"In":[0,48,60],"this":[1],"paper,":[2],"we":[3,93],"propose":[4],"a":[5,28,40,44],"novel":[6],"unsupervised":[7],"deep":[8,123,144],"learning":[9,124],"model,":[10],"called":[11],"PCA-based":[12],"Convolutional":[13],"Network":[14],"(PCN).":[15],"The":[16,110],"architecture":[17],"of":[18,22],"PCN":[19,114,137],"is":[20,67,130,138],"composed":[21],"several":[23],"feature":[24,34,45,81],"extraction":[25,35],"stages":[26],"and":[27,43,107],"nonlinear":[29,62],"output":[30,63],"stage.":[31,89],"Particularly,":[32],"each":[33],"stage":[36],"includes":[37],"two":[38],"layers:":[39],"convolutional":[41,50,72],"layer":[42],"pooling":[46],"layer.":[47],"the":[49,52,61,70,74,80,87],"layer,":[51],"filter":[53,75],"banks":[54,76],"are":[55,77],"simply":[56],"learned":[57,78],"by":[58],"PCA.":[59],"stage,":[64],"binary":[65],"hashing":[66],"applied.":[68],"For":[69],"higher":[71],"layers,":[73],"from":[79],"maps":[82],"that":[83,113],"were":[84],"obtained":[85],"in":[86],"previous":[88],"To":[90],"test":[91],"PCN,":[92],"conducted":[94],"extensive":[95],"experiments":[96],"on":[97],"some":[98],"challenging":[99],"tasks,":[100],"including":[101],"handwritten":[102],"digits":[103],"recognition,":[104],"face":[105],"recognition":[106],"texture":[108],"classification.":[109],"results":[111],"show":[112],"performs":[115],"competitive":[116],"with":[117],"or":[118],"even":[119],"better":[120],"than":[121,142],"state-of-the-art":[122],"models.":[125],"More":[126],"importantly,":[127],"since":[128],"there":[129],"no":[131],"back":[132],"propagation":[133],"for":[134],"supervised":[135],"finetuning,":[136],"much":[139],"more":[140],"efficient":[141],"existing":[143],"networks.":[145]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":6},{"year":2017,"cited_by_count":1}],"updated_date":"2026-11-10T11:39:43.021295","created_date":"2016-06-24T00:00:00"}
