{"id":"https://openalex.org/W1997436716","doi":"https://doi.org/10.1109/iciinfs.2014.7036543","title":"DT- CWT sub-band partitioning for face recognition","display_name":"DT- CWT sub-band partitioning for face recognition","publication_year":2014,"publication_date":"2014-12-01","ids":{"openalex":"https://openalex.org/W1997436716","doi":"https://doi.org/10.1109/iciinfs.2014.7036543","mag":"1997436716"},"language":"en","primary_location":{"id":"doi:10.1109/iciinfs.2014.7036543","doi":"https://doi.org/10.1109/iciinfs.2014.7036543","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iciinfs.2014.7036543","pdf_url":null,"source":{"id":"https://openalex.org/S7407088469","display_name":"IEEE International Conference on Industrial and Information Systems (ICIIS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 9th International Conference on Industrial and Information Systems (ICIIS)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"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/A5016125222","display_name":"Kothapelli Punnam Chandar","orcid":"https://orcid.org/0000-0002-9792-110X","observed_orcids":["https://orcid.org/0000-0002-9792-110X"]},"institutions":[{"id":"https://openalex.org/I28210344","display_name":"Kakatiya University","ror":"https://ror.org/012zpbg81","country_code":"IN","type":"education","lineage":["https://openalex.org/I28210344"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"K. Punnam Chandar","raw_affiliation_strings":["Electronics and Comm. Dept., Kakatiya University, Warangal, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Electronics and Comm. Dept., Kakatiya University, Warangal, India","institution_ids":["https://openalex.org/I28210344"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080206742","display_name":"T. Satyasavithri","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I10874241","display_name":"Jawaharlal Nehru Technological University, Hyderabad","ror":"https://ror.org/002tchr49","country_code":"IN","type":"education","lineage":["https://openalex.org/I10874241"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"T. Satyasavithri","raw_affiliation_strings":["Electronics and Comm. Dept., Jawaharlal Nehru Technological Univ., Hyderabad, INDIA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Electronics and Comm. Dept., Jawaharlal Nehru Technological Univ., Hyderabad, INDIA","institution_ids":["https://openalex.org/I10874241"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":87,"max":93},"biblio":{"volume":"22","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","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"}},"topics":[{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","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"}},{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.00039999998989515007,"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/T10828","display_name":"Biometric Identification and Security","score":9.999999747378752e-05,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/face-recognition","display_name":"face recognition","score":0.9300000071525574},{"id":"https://openalex.org/keywords/dual-tree-complex-wavelet-transform","display_name":"dual-tree complex wavelet transform","score":0.9779999852180481},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"principal component analysis","score":0.972000002861023},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"dimensionality reduction","score":0.8880000114440918},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"feature extraction","score":0.5979999899864197},{"id":"https://openalex.org/keywords/translation-invariance","display_name":"translation invariance","score":0.7990000247955322},{"id":"https://openalex.org/keywords/k-nearest-neighbors","display_name":"k-nearest neighbors","score":0.5789999961853027},{"id":"https://openalex.org/keywords/orl-face-database","display_name":"ORL face database","score":0.753000020980835}],"concepts":[{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7950283288955688},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7779941558837891},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.6939371824264526},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.6353850364685059},{"id":"https://openalex.org/C2777885455","wikidata":"https://www.wikidata.org/wiki/Q5156615","display_name":"Complex wavelet transform","level":5,"score":0.6209051609039307},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6044203639030457},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.5294613242149353},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5209451913833618},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.5110312700271606},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.5017778873443604},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.4806467592716217},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.4389289319515228},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.4251609444618225},{"id":"https://openalex.org/C2221639","wikidata":"https://www.wikidata.org/wiki/Q2877","display_name":"Discrete cosine transform","level":3,"score":0.41184505820274353},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.38492998480796814},{"id":"https://openalex.org/C46286280","wikidata":"https://www.wikidata.org/wiki/Q2414958","display_name":"Discrete wavelet transform","level":4,"score":0.3724209666252136},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3087151050567627},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iciinfs.2014.7036543","doi":"https://doi.org/10.1109/iciinfs.2014.7036543","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iciinfs.2014.7036543","pdf_url":null,"source":{"id":"https://openalex.org/S7407088469","display_name":"IEEE International Conference on Industrial and Information Systems (ICIIS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 9th International Conference on Industrial and Information Systems (ICIIS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1569310811","https://openalex.org/W1598106187","https://openalex.org/W1967599142","https://openalex.org/W1972610381","https://openalex.org/W1979743748","https://openalex.org/W1985809919","https://openalex.org/W1989702938","https://openalex.org/W2001619934","https://openalex.org/W2006218581","https://openalex.org/W2018332268","https://openalex.org/W2031802401","https://openalex.org/W2071128523","https://openalex.org/W2077878786","https://openalex.org/W2077883016","https://openalex.org/W2103280265","https://openalex.org/W2107596396","https://openalex.org/W2116019577","https://openalex.org/W2128848833","https://openalex.org/W2134262590","https://openalex.org/W2138451337","https://openalex.org/W2142425758","https://openalex.org/W2143304877","https://openalex.org/W2146076056","https://openalex.org/W2158114849","https://openalex.org/W2163808566","https://openalex.org/W2165731615"],"related_works":["https://openalex.org/W2101634409","https://openalex.org/W2013627044","https://openalex.org/W266450035","https://openalex.org/W1972610381","https://openalex.org/W2373146287","https://openalex.org/W7171326666","https://openalex.org/W1997405200","https://openalex.org/W2352079147","https://openalex.org/W2386917060","https://openalex.org/W2127798525"],"abstract_inverted_index":{"Principal":[0],"Component":[1],"analysis":[2,139],"extracts":[3],"the":[4,7,12,17,29,36,42,61,71,74,78,85,95,99,103,115,189,192,214,218,221],"features":[5],"from":[6,125],"low":[8,126],"frequency":[9,31,50,110,127,130],"content":[10],"of":[11,60,73,84,168,191,213,220],"face":[13,18,43,62,100,169,215],"image":[14,44,104],"and":[15,81],"performs":[16],"recognition":[19,37],"with":[20,153,173,183],"minimal":[21],"reconstruction":[22],"error.":[23],"This":[24,57],"statistical":[25],"method":[26],"de":[27],"emphasizes":[28],"high":[30,129],"information,":[32],"available":[33,68],"to":[34,48,54,108,128,131,195],"improve":[35],"performance.":[38],"In":[39],"this":[40,92],"paper,":[41],"is":[45,94,105,140,171],"partitioned":[46,106,116],"in":[47,65,107,160],"different":[49,109],"sub":[51,111,117],"bands":[52,112,118],"prior":[53,58,194,211],"PCA":[55,138,223],"analysis.":[56],"partitioning":[59,98,167,175,212],"image,":[63],"results":[64],"more":[66],"information":[67],"for":[69,97],"improving":[70],"performance":[72,219],"PCA.":[75,186],"Motivated":[76],"by":[77],"shift":[79],"invariance":[80],"Directional":[82],"property":[83],"Dual":[86],"Tree":[87],"Complex":[88],"Wavelet":[89],"transform":[90],"(DT-CWT),":[91],"technique":[93],"choice":[96],"images.":[101],"First,":[102],"using":[113,148],"DT-CWT,":[114],"are":[119,146,158,203],"arranged":[120],"as":[121,185],"a":[122,133],"column":[123],"vector":[124],"form":[132],"novel":[134],"OneS":[135],"representation.":[136],"Further,":[137],"performed.":[141],"The":[142,165,205],"resultant":[143],"feature":[144],"vectors":[145],"classified":[147],"k":[149],"nearest":[150],"neighbor":[151],"classifier":[152],"Maholanobis":[154],"cosine":[155],"distance.":[156],"Simulations":[157],"performed":[159],"Matlab,":[161],"on":[162],"ORL":[163],"Database.":[164],"DTCWT":[166],"images":[170,216],"compared":[172],"other":[174],"techniques":[176],"like,":[177],"Discrete":[178],"Wavelets":[179],"`db2'":[180],"&":[181],"`coif2',":[182],"baseline":[184],"To":[187],"show":[188],"efficacy":[190],"partitioning,":[193],"dimensionality":[196,224],"reduction,":[197],"Detection":[198],"error":[199],"tradeoff":[200],"(DET)":[201],"curves":[202,207],"computed.":[204],"DET":[206],"obtained":[208],"shows":[209],"that":[210],"improves":[217],"further":[222],"reduction.":[225]},"counts_by_year":[{"year":2021,"cited_by_count":1}],"updated_date":"2026-10-30T12:39:25.321706","created_date":"2016-06-24T00:00:00"}
