{"id":"https://openalex.org/W2033278531","doi":"https://doi.org/10.1109/icip.2013.6738681","title":"Compressive Distance Classifier Correlation Filter","display_name":"Compressive Distance Classifier Correlation Filter","publication_year":2013,"publication_date":"2013-09-01","ids":{"openalex":"https://openalex.org/W2033278531","doi":"https://doi.org/10.1109/icip.2013.6738681","mag":"2033278531"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2013.6738681","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2013.6738681","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE International Conference on Image Processing","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/A5030489357","display_name":"Karthik Mahesh Varadarajan","orcid":null},"institutions":[{"id":"https://openalex.org/I129774422","display_name":"University of Vienna","ror":"https://ror.org/03prydq77","country_code":"AT","type":"education","lineage":["https://openalex.org/I129774422"]},{"id":"https://openalex.org/I145847075","display_name":"TU Wien","ror":"https://ror.org/04d836q62","country_code":"AT","type":"education","lineage":["https://openalex.org/I145847075"]}],"countries":["AT"],"is_corresponding":true,"raw_author_name":"Karthik Mahesh Varadarajan","raw_affiliation_strings":["Technical University of Vienna","Tech. Univ. of Vienna, Vienna, Austria"],"affiliations":[{"raw_affiliation_string":"Technical University of Vienna","institution_ids":["https://openalex.org/I129774422"]},{"raw_affiliation_string":"Tech. Univ. of Vienna, Vienna, Austria","institution_ids":["https://openalex.org/I145847075","https://openalex.org/I129774422"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5013565399","display_name":"Markus Vincze","orcid":"https://orcid.org/0000-0002-2799-491X"},"institutions":[{"id":"https://openalex.org/I129774422","display_name":"University of Vienna","ror":"https://ror.org/03prydq77","country_code":"AT","type":"education","lineage":["https://openalex.org/I129774422"]},{"id":"https://openalex.org/I145847075","display_name":"TU Wien","ror":"https://ror.org/04d836q62","country_code":"AT","type":"education","lineage":["https://openalex.org/I145847075"]}],"countries":["AT"],"is_corresponding":false,"raw_author_name":"Markus Vincze","raw_affiliation_strings":["Technical University of Vienna","Tech. Univ. of Vienna, Vienna, Austria"],"affiliations":[{"raw_affiliation_string":"Technical University of Vienna","institution_ids":["https://openalex.org/I129774422"]},{"raw_affiliation_string":"Tech. Univ. of Vienna, Vienna, Austria","institution_ids":["https://openalex.org/I145847075","https://openalex.org/I129774422"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5030489357"],"corresponding_institution_ids":["https://openalex.org/I129774422","https://openalex.org/I145847075"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.09741766,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3307","last_page":"3311"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998999834060669,"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/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9904999732971191,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"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/T12676","display_name":"Machine Learning and ELM","score":0.9900000095367432,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.613088846206665},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.5992687344551086},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5517480373382568},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5157211422920227},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5109273791313171},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.4436115026473999},{"id":"https://openalex.org/keywords/restricted-isometry-property","display_name":"Restricted isometry property","score":0.43888455629348755},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.43430009484291077},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.4306446313858032},{"id":"https://openalex.org/keywords/matched-filter","display_name":"Matched filter","score":0.4145643711090088},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.38973569869995117},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.314743310213089}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.613088846206665},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.5992687344551086},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5517480373382568},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5157211422920227},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5109273791313171},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.4436115026473999},{"id":"https://openalex.org/C17902559","wikidata":"https://www.wikidata.org/wiki/Q17099734","display_name":"Restricted isometry property","level":3,"score":0.43888455629348755},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.43430009484291077},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.4306446313858032},{"id":"https://openalex.org/C50151734","wikidata":"https://www.wikidata.org/wiki/Q1759577","display_name":"Matched filter","level":3,"score":0.4145643711090088},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.38973569869995117},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.314743310213089},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2013.6738681","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2013.6738681","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE International Conference on Image Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W94937181","https://openalex.org/W1521499940","https://openalex.org/W2067726040","https://openalex.org/W2081889909","https://openalex.org/W2082476922","https://openalex.org/W2099641086","https://openalex.org/W2116872728","https://openalex.org/W2126131432","https://openalex.org/W2129638195","https://openalex.org/W2129812935","https://openalex.org/W2141155793","https://openalex.org/W2145096794","https://openalex.org/W2296616510","https://openalex.org/W2539491362","https://openalex.org/W4250955649","https://openalex.org/W6603878980","https://openalex.org/W6630955567","https://openalex.org/W6678689058","https://openalex.org/W6681058996"],"related_works":["https://openalex.org/W1595179898","https://openalex.org/W2949399405","https://openalex.org/W4301619540","https://openalex.org/W4297570801","https://openalex.org/W1639246335","https://openalex.org/W116214155","https://openalex.org/W2952050240","https://openalex.org/W2568623927","https://openalex.org/W2085436476","https://openalex.org/W2025666718"],"abstract_inverted_index":{"Compressed":[0],"Sensing":[1],"(CS)":[2],"is":[3,60,76,148,175,186],"seen":[4],"as":[5,16],"the":[6,10,23,40,53,71,84,87,103,116,128,133,141,151,157,161,169,172,194,207,211],"pathway":[7],"to":[8],"increase":[9,190],"efficiency":[11],"of":[12,42,86,112,156,171,199,210],"sensor":[13,43],"systems":[14,44],"such":[15],"MRI,":[17],"SAR":[18],"and":[19,26,45,100,147,160,204],"SAS":[20],"while":[21,139],"avoiding":[22],"huge":[24],"costs":[25],"related":[27,46],"processing":[28],"accompanying":[29],"high-resolution":[30],"data":[31,183],"acquisition.":[32],"While":[33],"there":[34],"has":[35],"been":[36],"a":[37,61,77,109,125,179,188],"surge":[38],"in":[39,52,67,97,102,127,191],"number":[41],"algorithms":[47],"using":[48],"CS,":[49],"target/object":[50],"recognition":[51],"sensing":[54],"domain":[55,130],"which":[56,75,123,185],"offers":[57,108],"numerous":[58],"advantages,":[59],"rather":[62],"nascent":[63],"field.":[64],"The":[65],"state-of-the-art":[66],"this":[68],"field":[69],"includes":[70],"Smashed":[72],"Filter":[73,121],"(SF),":[74],"reduced":[78],"dimensionality":[79],"maximum":[80],"likelihood":[81],"classifier.":[82],"Nevertheless,":[83],"accuracy":[85,170,192],"filter":[88,113,174],"remains":[89],"low":[90],"for":[91],"practical":[92],"applications,":[93],"especially":[94],"with":[95],"variations":[96],"scale,":[98],"translation":[99],"rotation":[101],"test":[104,182],"data.":[105],"This":[106],"paper":[107],"new":[110],"type":[111],"-":[114],"called":[115],"Compressive":[117],"Distance":[118],"Classifier":[119],"Correlation":[120],"(CDCCF),":[122],"applies":[124],"transformation":[126],"CS":[129],"thereby":[131],"increasing":[132],"distance":[134,142],"between":[135,143],"intra-class":[136],"correlation":[137,145],"peaks":[138,146],"reducing":[140],"inter-class":[144],"based":[149],"on":[150,178],"Restricted":[152],"Isometry":[153],"Property":[154],"(RIP)":[155],"compressed":[158],"manifold":[159],"Johnson":[162],"Lindenstrauss":[163],"Lemma.":[164],"Results":[165],"presented":[166],"show":[167],"that":[168],"CDCCF":[173],"about":[176],"70%":[177],"12":[180],"class":[181],"set,":[184],"over":[187,193,213],"two-fold":[189],"SF.":[195],"Confusion":[196],"matrices,":[197],"measures":[198],"ROC,":[200],"Mean":[201],"Average":[202],"Precision":[203],"Accuracy":[205],"demonstrate":[206],"robust":[208],"performance":[209],"algorithm":[212],"SF":[214],"across":[215],"different":[216],"compressive":[217],"sampling":[218],"resolutions.":[219]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
