{"id":"https://openalex.org/W2121744339","doi":"https://doi.org/10.1109/cvpr.2008.4587439","title":"Unsupervised estimation of segmentation quality using nonnegative factorization","display_name":"Unsupervised estimation of segmentation quality using nonnegative factorization","publication_year":2008,"publication_date":"2008-06-01","ids":{"openalex":"https://openalex.org/W2121744339","doi":"https://doi.org/10.1109/cvpr.2008.4587439","mag":"2121744339"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr.2008.4587439","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2008.4587439","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 IEEE Conference on Computer Vision and Pattern Recognition","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/A5085024213","display_name":"Roman Sandler","orcid":"https://orcid.org/0000-0002-4074-1714"},"institutions":[{"id":"https://openalex.org/I174306211","display_name":"Technion \u2013 Israel Institute of Technology","ror":"https://ror.org/03qryx823","country_code":"IL","type":"education","lineage":["https://openalex.org/I174306211"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Roman Sandler","raw_affiliation_strings":["Computer Science Department, Technion-Israel Institute of Technology, Haifa, Israel","Comput. Sci. Dept., Technion, Haifa"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science Department, Technion-Israel Institute of Technology, Haifa, Israel","institution_ids":["https://openalex.org/I174306211"]},{"raw_affiliation_string":"Comput. Sci. Dept., Technion, Haifa","institution_ids":["https://openalex.org/I174306211"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072392744","display_name":"Michael Lindenbaum","orcid":null},"institutions":[{"id":"https://openalex.org/I174306211","display_name":"Technion \u2013 Israel Institute of Technology","ror":"https://ror.org/03qryx823","country_code":"IL","type":"education","lineage":["https://openalex.org/I174306211"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Michael Lindenbaum","raw_affiliation_strings":["Computer Science Department, Technion-Israel Institute of Technology, Haifa, Israel","Comput. Sci. Dept., Technion, Haifa"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science Department, Technion-Israel Institute of Technology, Haifa, Israel","institution_ids":["https://openalex.org/I174306211"]},{"raw_affiliation_string":"Comput. Sci. Dept., Technion, Haifa","institution_ids":["https://openalex.org/I174306211"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.71,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.74738964,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"13","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9994999766349792,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9994999766349792,"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":0.9959999918937683,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9958999752998352,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7238372564315796},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.686620831489563},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6569566130638123},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6325619220733643},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5702698826789856},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5614050030708313},{"id":"https://openalex.org/keywords/non-negative-matrix-factorization","display_name":"Non-negative matrix factorization","score":0.5529348254203796},{"id":"https://openalex.org/keywords/precision-and-recall","display_name":"Precision and recall","score":0.5521173477172852},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.541581928730011},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4483731985092163},{"id":"https://openalex.org/keywords/smoothness","display_name":"Smoothness","score":0.44664838910102844},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.4335383176803589},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.32297688722610474},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.26962578296661377}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7238372564315796},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.686620831489563},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6569566130638123},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6325619220733643},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5702698826789856},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5614050030708313},{"id":"https://openalex.org/C152671427","wikidata":"https://www.wikidata.org/wiki/Q10843505","display_name":"Non-negative matrix factorization","level":4,"score":0.5529348254203796},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.5521173477172852},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.541581928730011},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4483731985092163},{"id":"https://openalex.org/C102634674","wikidata":"https://www.wikidata.org/wiki/Q868473","display_name":"Smoothness","level":2,"score":0.44664838910102844},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.4335383176803589},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.32297688722610474},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.26962578296661377},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"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/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cvpr.2008.4587439","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2008.4587439","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 IEEE Conference on Computer Vision and Pattern Recognition","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4699999988079071,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W1528124813","https://openalex.org/W2017288758","https://openalex.org/W2037563221","https://openalex.org/W2059269831","https://openalex.org/W2059745395","https://openalex.org/W2067191022","https://openalex.org/W2081356243","https://openalex.org/W2089948116","https://openalex.org/W2104125540","https://openalex.org/W2107290706","https://openalex.org/W2108299137","https://openalex.org/W2111498234","https://openalex.org/W2111692787","https://openalex.org/W2114487471","https://openalex.org/W2119823327","https://openalex.org/W2121927366","https://openalex.org/W2135029798","https://openalex.org/W2140318696","https://openalex.org/W2141376824","https://openalex.org/W2148347694","https://openalex.org/W2148861411","https://openalex.org/W2152695155","https://openalex.org/W2153394113","https://openalex.org/W2156808562","https://openalex.org/W2159372453","https://openalex.org/W2162023479","https://openalex.org/W2168446235","https://openalex.org/W2169551590","https://openalex.org/W2296770417","https://openalex.org/W3143596294","https://openalex.org/W4234989890","https://openalex.org/W6676584123","https://openalex.org/W6680012447","https://openalex.org/W6680770193","https://openalex.org/W6682949822","https://openalex.org/W6991377603"],"related_works":["https://openalex.org/W2127243424","https://openalex.org/W4390394189","https://openalex.org/W2037504162","https://openalex.org/W2539013788","https://openalex.org/W2792706544","https://openalex.org/W1568451138","https://openalex.org/W2156699640","https://openalex.org/W2045265907","https://openalex.org/W2972997031","https://openalex.org/W34555840"],"abstract_inverted_index":{"We":[0],"propose":[1],"an":[2],"unsupervised":[3,179],"method":[4],"for":[5,71],"evaluating":[6,15],"image":[7,80,123,143],"segmentation.":[8],"Common":[9],"methods":[10,41],"are":[11,96,115,135],"typically":[12],"based":[13,116,164],"on":[14,42,77,117,128,165],"smoothness":[16],"within":[17],"segments":[18,85],"and":[19,23,46,126],"contrast":[20],"between":[21],"them,":[22],"the":[24,84,112,121,146,153,156,178,182],"measure":[25,180],"they":[26],"provide":[27],"is":[28,110,170],"not":[29,127],"explicitly":[30],"related":[31],"to":[32,131,138,161],"segmentation":[33,60,175],"errors.":[34],"The":[35,93],"proposed":[36],"approach":[37],"differs":[38],"from":[39],"these":[40],"several":[43,48],"important":[44,108],"points":[45],"has":[47],"advantages":[49],"over":[50],"them.":[51],"First,":[52],"it":[53,75,169],"provides":[54],"a":[55,78,87,100,129,174,188],"meaningful,":[56],"quantitative":[57],"assessment":[58],"of":[59,89,120,148,155],"quality,":[61],"in":[62,159],"precision/recall":[63,94,157],"terms,":[64],"which":[65,82,114],"were":[66],"applicable":[67],"so":[68],"far":[69],"only":[70],"supervised":[72,189],"evaluation.":[73],"Second,":[74],"builds":[76],"new":[79],"model,":[81],"characterizes":[83],"as":[86,142],"mixture":[88],"basic":[90],"feature":[91],"distributions.":[92],"estimates":[95,158],"then":[97],"obtained":[98],"by":[99,187],"nonnegative":[101],"matrix":[102],"factorization":[103],"(NMF)":[104],"process.":[105],"A":[106],"third":[107],"advantage":[109],"that":[111,172],"estimates,":[113],"intrinsic":[118],"properties":[119],"specific":[122],"being":[124],"evaluated":[125],"comparison":[130,160],"typical":[132],"images":[133],"(learning),":[134],"relatively":[136],"robust":[137],"context":[139],"factors":[140],"such":[141],"quality":[144,184],"or":[145],"presence":[147],"texture.":[149],"Experimental":[150],"results":[151],"demonstrate":[152],"accuracy":[154],"ground":[162],"truth":[163],"human":[166],"judgment.":[167],"Moreover,":[168],"shown":[171],"tuning":[173],"algorithm":[176],"using":[177],"improves":[181],"algorithm's":[183],"(as":[185],"measured":[186],"method).":[190]},"counts_by_year":[{"year":2021,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
