{"id":"https://openalex.org/W2103729542","doi":"https://doi.org/10.1109/icassp.2009.4959743","title":"Robust detection of a set of outliers for image changes based on rerunning the regression","display_name":"Robust detection of a set of outliers for image changes based on rerunning the regression","publication_year":2009,"publication_date":"2009-04-01","ids":{"openalex":"https://openalex.org/W2103729542","doi":"https://doi.org/10.1109/icassp.2009.4959743","mag":"2103729542"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2009.4959743","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2009.4959743","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE International Conference on Acoustics, Speech and Signal 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/A5100617792","display_name":"Dong Sik Kim","orcid":"https://orcid.org/0000-0002-1001-169X"},"institutions":[{"id":"https://openalex.org/I83436808","display_name":"Hankuk University of Foreign Studies","ror":"https://ror.org/051q2m369","country_code":"KR","type":"education","lineage":["https://openalex.org/I83436808"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Dong Sik Kim","raw_affiliation_strings":["School of Electronics and Information Engineering, Hankuk University of Foreign Studies, Gyonggi-do, 449-791, Korea","School of Electronics and Information Engineering, Hankuk University of Foreign Studies, Gyonggi-do, 449-791, Korea#TAB#"],"affiliations":[{"raw_affiliation_string":"School of Electronics and Information Engineering, Hankuk University of Foreign Studies, Gyonggi-do, 449-791, Korea","institution_ids":["https://openalex.org/I83436808"]},{"raw_affiliation_string":"School of Electronics and Information Engineering, Hankuk University of Foreign Studies, Gyonggi-do, 449-791, Korea#TAB#","institution_ids":["https://openalex.org/I83436808"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5100617792"],"corresponding_institution_ids":["https://openalex.org/I83436808"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.15142552,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"953","last_page":"956"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11871","display_name":"Advanced Statistical Methods and Models","score":0.995199978351593,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11871","display_name":"Advanced Statistical Methods and Models","score":0.995199978351593,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9779999852180481,"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"}},{"id":"https://openalex.org/T13114","display_name":"Image Processing Techniques and Applications","score":0.9736999869346619,"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/outlier","display_name":"Outlier","score":0.873724102973938},{"id":"https://openalex.org/keywords/robust-regression","display_name":"Robust regression","score":0.7159717679023743},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6089760661125183},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.605812668800354},{"id":"https://openalex.org/keywords/polynomial-regression","display_name":"Polynomial regression","score":0.5905986428260803},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5257038474082947},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5216820240020752},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.5031420588493347},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5001957416534424},{"id":"https://openalex.org/keywords/compensation","display_name":"Compensation (psychology)","score":0.47954604029655457},{"id":"https://openalex.org/keywords/linear-regression","display_name":"Linear regression","score":0.4675421118736267},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.4653886556625366},{"id":"https://openalex.org/keywords/variance","display_name":"Variance (accounting)","score":0.46385976672172546},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.45424896478652954},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.43164923787117004},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.42478618025779724},{"id":"https://openalex.org/keywords/polynomial","display_name":"Polynomial","score":0.4120176136493683},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.35273832082748413},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.32099711894989014},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.21993249654769897},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.1311817169189453}],"concepts":[{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.873724102973938},{"id":"https://openalex.org/C70259352","wikidata":"https://www.wikidata.org/wiki/Q1847839","display_name":"Robust regression","level":3,"score":0.7159717679023743},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6089760661125183},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.605812668800354},{"id":"https://openalex.org/C120068334","wikidata":"https://www.wikidata.org/wiki/Q45343","display_name":"Polynomial regression","level":3,"score":0.5905986428260803},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5257038474082947},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5216820240020752},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.5031420588493347},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5001957416534424},{"id":"https://openalex.org/C2780023022","wikidata":"https://www.wikidata.org/wiki/Q1338171","display_name":"Compensation (psychology)","level":2,"score":0.47954604029655457},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.4675421118736267},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.4653886556625366},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.46385976672172546},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.45424896478652954},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.43164923787117004},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.42478618025779724},{"id":"https://openalex.org/C90119067","wikidata":"https://www.wikidata.org/wiki/Q43260","display_name":"Polynomial","level":2,"score":0.4120176136493683},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.35273832082748413},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.32099711894989014},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.21993249654769897},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.1311817169189453},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"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/C11171543","wikidata":"https://www.wikidata.org/wiki/Q41630","display_name":"Psychoanalysis","level":1,"score":0.0},{"id":"https://openalex.org/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.2009.4959743","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2009.4959743","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE International Conference on Acoustics, Speech and Signal Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4099999964237213,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W147723833","https://openalex.org/W2048997388","https://openalex.org/W2113161761","https://openalex.org/W2135902042","https://openalex.org/W2797431976","https://openalex.org/W4206495155","https://openalex.org/W4245193022","https://openalex.org/W4256068510"],"related_works":["https://openalex.org/W2499612753","https://openalex.org/W3111802945","https://openalex.org/W2946096271","https://openalex.org/W2295423552","https://openalex.org/W3107369729","https://openalex.org/W3121734683","https://openalex.org/W4210813465","https://openalex.org/W2085680114","https://openalex.org/W1600426151","https://openalex.org/W4311044804"],"abstract_inverted_index":{"By":[0],"comparing":[1],"two":[2],"images,":[3,35],"which":[4,40],"are":[5],"captured":[6],"with":[7],"the":[8,17,26,29,34,44,57,69,76,81,88,91,94,103,111,116],"same":[9],"scene":[10],"at":[11],"different":[12,30],"times,":[13],"we":[14],"can":[15],"detect":[16],"image":[18],"changes":[19],"due":[20],"to":[21,115],"moving":[22],"objects.":[23],"To":[24],"reduce":[25],"influence":[27,58],"from":[28,59],"intensity":[31,37],"properties":[32],"of":[33,54,62,90,93,118],"an":[36,51,98],"compensation":[38,100,109],"scheme,":[39],"is":[41,48,71,83,105],"based":[42],"on":[43],"polynomial":[45],"regression":[46,70,82],"model,":[47],"employed.":[49,72],"For":[50],"accurate":[52],"detection":[53,112],"outliers":[55],"alleviating":[56],"a":[60,64],"set":[61],"outliers,":[63],"simple":[65],"technique":[66],"that":[67,78],"reruns":[68,80],"In":[73],"this":[74],"paper,":[75],"algorithm":[77,113],"iteratively":[79],"theoretically":[84],"analyzed":[85],"by":[86],"observing":[87],"convergency":[89],"estimates":[92],"noise":[95],"variance.":[96],"Using":[97],"empirical":[99],"constant":[101],"for":[102,120],"estimate":[104],"also":[106],"proposed.":[107],"The":[108],"enables":[110],"robust":[114],"choice":[117],"thresholds":[119],"selecting":[121],"outliers.":[122]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}