{"id":"https://openalex.org/W2355765288","doi":"https://doi.org/10.1109/ijcnn.2016.7727306","title":"A theoretical analysis of Deep Neural Networks for texture classification","display_name":"A theoretical analysis of Deep Neural Networks for texture classification","publication_year":2016,"publication_date":"2016-07-01","ids":{"openalex":"https://openalex.org/W2355765288","doi":"https://doi.org/10.1109/ijcnn.2016.7727306","mag":"2355765288"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2016.7727306","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2016.7727306","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1605.02699","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102782582","display_name":"Saikat Basu","orcid":"https://orcid.org/0000-0001-6590-3938"},"institutions":[{"id":"https://openalex.org/I121820613","display_name":"Louisiana State University","ror":"https://ror.org/05ect4e57","country_code":"US","type":"education","lineage":["https://openalex.org/I121820613"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Saikat Basu","raw_affiliation_strings":["Louisiana State University"],"affiliations":[{"raw_affiliation_string":"Louisiana State University","institution_ids":["https://openalex.org/I121820613"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000103239","display_name":"Manohar Karki","orcid":"https://orcid.org/0000-0002-0353-9728"},"institutions":[{"id":"https://openalex.org/I121820613","display_name":"Louisiana State University","ror":"https://ror.org/05ect4e57","country_code":"US","type":"education","lineage":["https://openalex.org/I121820613"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Manohar Karki","raw_affiliation_strings":["Louisiana State University"],"affiliations":[{"raw_affiliation_string":"Louisiana State University","institution_ids":["https://openalex.org/I121820613"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101963514","display_name":"Supratik Mukhopadhyay","orcid":"https://orcid.org/0000-0003-0839-1133"},"institutions":[{"id":"https://openalex.org/I121820613","display_name":"Louisiana State University","ror":"https://ror.org/05ect4e57","country_code":"US","type":"education","lineage":["https://openalex.org/I121820613"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Supratik Mukhopadhyay","raw_affiliation_strings":["Louisiana State University"],"affiliations":[{"raw_affiliation_string":"Louisiana State University","institution_ids":["https://openalex.org/I121820613"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007681565","display_name":"Sangram Ganguly","orcid":"https://orcid.org/0000-0002-5916-1410"},"institutions":[{"id":"https://openalex.org/I1280536761","display_name":"Ames Research Center","ror":"https://ror.org/02acart68","country_code":"US","type":"facility","lineage":["https://openalex.org/I1280536761","https://openalex.org/I4210124779"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sangram Ganguly","raw_affiliation_strings":["NASA Ames Research Center"],"affiliations":[{"raw_affiliation_string":"NASA Ames Research Center","institution_ids":["https://openalex.org/I1280536761"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073341246","display_name":"Ramakrishna Nemani","orcid":"https://orcid.org/0000-0002-0883-1517"},"institutions":[{"id":"https://openalex.org/I1280536761","display_name":"Ames Research Center","ror":"https://ror.org/02acart68","country_code":"US","type":"facility","lineage":["https://openalex.org/I1280536761","https://openalex.org/I4210124779"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ramakrishna Nemani","raw_affiliation_strings":["NASA Ames Research Center"],"affiliations":[{"raw_affiliation_string":"NASA Ames Research Center","institution_ids":["https://openalex.org/I1280536761"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022141765","display_name":"Robert DiBiano","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Robert DiBiano","raw_affiliation_strings":["Autopredictive Coding LLC"],"affiliations":[{"raw_affiliation_string":"Autopredictive Coding LLC","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058839665","display_name":"Shreekant Gayaka","orcid":null},"institutions":[{"id":"https://openalex.org/I4210165146","display_name":"Applied Materials (Germany)","ror":"https://ror.org/05ejpyv46","country_code":"DE","type":"company","lineage":["https://openalex.org/I193427800","https://openalex.org/I4210165146"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Shreekant Gayaka","raw_affiliation_strings":["Applied Materials"],"affiliations":[{"raw_affiliation_string":"Applied Materials","institution_ids":["https://openalex.org/I4210165146"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5102782582"],"corresponding_institution_ids":["https://openalex.org/I121820613"],"apc_list":null,"apc_paid":null,"fwci":1.0168,"has_fulltext":true,"cited_by_count":8,"citation_normalized_percentile":{"value":0.82750926,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"992","last_page":"999"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9983999729156494,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9983999729156494,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9972000122070312,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.996999979019165,"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/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7945612668991089},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6837992072105408},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5483038425445557},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5459323525428772},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.5359683036804199},{"id":"https://openalex.org/keywords/centroid","display_name":"Centroid","score":0.5347766876220703},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.498629093170166},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.4761497974395752},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.46316397190093994},{"id":"https://openalex.org/keywords/intrinsic-dimension","display_name":"Intrinsic dimension","score":0.462674081325531},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4232296347618103},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.41040340065956116},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.09626451134681702}],"concepts":[{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7945612668991089},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6837992072105408},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5483038425445557},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5459323525428772},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.5359683036804199},{"id":"https://openalex.org/C146599234","wikidata":"https://www.wikidata.org/wiki/Q511093","display_name":"Centroid","level":2,"score":0.5347766876220703},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.498629093170166},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.4761497974395752},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.46316397190093994},{"id":"https://openalex.org/C30732413","wikidata":"https://www.wikidata.org/wiki/Q17092636","display_name":"Intrinsic dimension","level":3,"score":0.462674081325531},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4232296347618103},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.41040340065956116},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.09626451134681702}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/ijcnn.2016.7727306","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2016.7727306","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1605.02699","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1605.02699","pdf_url":"https://arxiv.org/pdf/1605.02699","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":"mag:2355765288","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1605.02699.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.1605.02699","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1605.02699","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1605.02699","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1605.02699","pdf_url":"https://arxiv.org/pdf/1605.02699","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":[{"display_name":"Reduced inequalities","score":0.7900000214576721,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306101","display_name":"National Aeronautics and Space Administration","ror":"https://ror.org/027ka1x80"},{"id":"https://openalex.org/F4320332374","display_name":"Ames Research Center","ror":"https://ror.org/02acart68"},{"id":"https://openalex.org/F4320338075","display_name":"Core Research for Evolutional Science and Technology","ror":"https://ror.org/00097mb19"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2355765288.pdf","grobid_xml":"https://content.openalex.org/works/W2355765288.grobid-xml"},"referenced_works_count":25,"referenced_works":["https://openalex.org/W51946390","https://openalex.org/W73877600","https://openalex.org/W1480376833","https://openalex.org/W1560641100","https://openalex.org/W1574384841","https://openalex.org/W1672197616","https://openalex.org/W2029538739","https://openalex.org/W2044465660","https://openalex.org/W2089947415","https://openalex.org/W2112796928","https://openalex.org/W2117539524","https://openalex.org/W2120888827","https://openalex.org/W2126833203","https://openalex.org/W2136922672","https://openalex.org/W2144242878","https://openalex.org/W2157169955","https://openalex.org/W2165533158","https://openalex.org/W2211843587","https://openalex.org/W2235604683","https://openalex.org/W2496126447","https://openalex.org/W3118608800","https://openalex.org/W4238284510","https://openalex.org/W6633570323","https://openalex.org/W6683389101","https://openalex.org/W6787972765"],"related_works":["https://openalex.org/W2963234238","https://openalex.org/W2999184797","https://openalex.org/W2102852560","https://openalex.org/W3202619440","https://openalex.org/W3019281874","https://openalex.org/W1601292208","https://openalex.org/W3177324614","https://openalex.org/W1835123606","https://openalex.org/W2063064098","https://openalex.org/W3015475128","https://openalex.org/W2896124229","https://openalex.org/W2204975001","https://openalex.org/W2113477426","https://openalex.org/W585462335","https://openalex.org/W2783359318","https://openalex.org/W2055346081","https://openalex.org/W2833435207","https://openalex.org/W2578369184","https://openalex.org/W2113498043","https://openalex.org/W2121380873"],"abstract_inverted_index":{"We":[0,151],"investigate":[1],"the":[2,9,30,33,43,49,67,81,87,102,122,154,158,161,174,178,185],"use":[3,48],"of":[4,11,32,51,90,108,115,177,184],"Deep":[5],"Neural":[6,92],"Networks":[7],"for":[8,19,36,80],"classification":[10],"image":[12],"datasets":[13,126,140],"where":[14],"texture":[15],"features":[16,40],"are":[17,127],"important":[18],"generating":[20],"class-conditional":[21],"discriminative":[22],"representations.":[23],"To":[24],"this":[25,76],"end,":[26],"we":[27,78],"first":[28,82],"derive":[29,79,153],"size":[31],"feature":[34,58],"space":[35,188],"some":[37],"standard":[38],"textural":[39],"extracted":[41],"from":[42,157],"input":[44],"dataset":[45],"and":[46,98,101,110,141,163,171],"then":[47,152],"theory":[50],"Vapnik-Chervonenkis":[52],"dimension":[53,89,117],"to":[54,75,120,133,145,160,190],"show":[55,172],"that":[56,124,173],"hand-crafted":[57],"extraction":[59],"creates":[60],"low-dimensional":[61],"representations":[62],"which":[63],"help":[64],"in":[65,167],"reducing":[66],"overall":[68],"excess":[69,105],"error":[70,106],"rate.":[71],"As":[72],"a":[73],"corollary":[74],"analysis,":[77],"time":[83],"upper":[84],"bounds":[85],"on":[86],"VC":[88],"Convolutional":[91],"Network":[93],"as":[94,96,131,182],"well":[95],"Dropout":[97,109],"Dropconnect":[99,111],"networks":[100],"relation":[103],"between":[104],"rate":[107],"networks.":[112,150],"The":[113],"concept":[114],"intrinsic":[116],"is":[118],"used":[119],"validate":[121],"intuition":[123],"texture-based":[125],"inherently":[128],"higher":[129],"dimensional":[130],"compared":[132],"handwritten":[134],"digits":[135],"or":[136],"other":[137],"object":[138],"recognition":[139],"hence":[142],"more":[143],"difficult":[144],"be":[146],"shattered":[147],"by":[148],"neural":[149],"mean":[155],"distance":[156],"centroid":[159],"nearest":[162],"farthest":[164],"sampling":[165],"points":[166],"an":[168],"n-dimensional":[169],"manifold":[170],"Relative":[175],"Contrast":[176],"sample":[179],"data":[180],"vanishes":[181],"dimensionality":[183],"underlying":[186],"vector":[187],"tends":[189],"infinity.":[191]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":4}],"updated_date":"2026-03-25T23:56:10.502304","created_date":"2025-10-10T00:00:00"}