{"id":"https://openalex.org/W2296005560","doi":"https://doi.org/10.1109/icip.2015.7351430","title":"Scale estimation with difference of ordered residuals","display_name":"Scale estimation with difference of ordered residuals","publication_year":2015,"publication_date":"2015-09-01","ids":{"openalex":"https://openalex.org/W2296005560","doi":"https://doi.org/10.1109/icip.2015.7351430","mag":"2296005560"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2015.7351430","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2015.7351430","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE International Conference on Image Processing (ICIP)","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/A5051410893","display_name":"Maria Scalzo-Cornacchia","orcid":null},"institutions":[{"id":"https://openalex.org/I70983195","display_name":"Syracuse University","ror":"https://ror.org/025r5qe02","country_code":"US","type":"education","lineage":["https://openalex.org/I70983195"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Maria Scalzo-Cornacchia","raw_affiliation_strings":["Dept of E.E.C.S., Syracuse University, Syracuse, New York, USA"],"affiliations":[{"raw_affiliation_string":"Dept of E.E.C.S., Syracuse University, Syracuse, New York, USA","institution_ids":["https://openalex.org/I70983195"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5004337702","display_name":"Senem Velipasalar","orcid":"https://orcid.org/0000-0002-1430-1555"},"institutions":[{"id":"https://openalex.org/I70983195","display_name":"Syracuse University","ror":"https://ror.org/025r5qe02","country_code":"US","type":"education","lineage":["https://openalex.org/I70983195"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Senem Velipasalar","raw_affiliation_strings":["Dept of E.E.C.S., Syracuse University, Syracuse, New York, USA"],"affiliations":[{"raw_affiliation_string":"Dept of E.E.C.S., Syracuse University, Syracuse, New York, USA","institution_ids":["https://openalex.org/I70983195"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5051410893"],"corresponding_institution_ids":["https://openalex.org/I70983195"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.16120757,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3377","last_page":"3381"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12549","display_name":"Image and Object Detection Techniques","score":0.9997000098228455,"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/T12549","display_name":"Image and Object Detection Techniques","score":0.9997000098228455,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9993000030517578,"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9991000294685364,"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":0.8404898643493652},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.7528141736984253},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.7412416338920593},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7138681411743164},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.6428608894348145},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.6104559302330017},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.5469735264778137},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4844055771827698},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.44760483503341675},{"id":"https://openalex.org/keywords/estimation-theory","display_name":"Estimation theory","score":0.42389652132987976},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.39192742109298706},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.34728091955184937},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.29296040534973145},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.26869791746139526},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07426819205284119}],"concepts":[{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.8404898643493652},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.7528141736984253},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.7412416338920593},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7138681411743164},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.6428608894348145},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.6104559302330017},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.5469735264778137},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4844055771827698},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44760483503341675},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.42389652132987976},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.39192742109298706},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34728091955184937},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.29296040534973145},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.26869791746139526},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07426819205284119},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2015.7351430","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2015.7351430","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE International Conference on Image Processing (ICIP)","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":13,"referenced_works":["https://openalex.org/W1974014252","https://openalex.org/W1984093092","https://openalex.org/W1997845072","https://openalex.org/W2113054345","https://openalex.org/W2114674762","https://openalex.org/W2122212542","https://openalex.org/W2134928129","https://openalex.org/W2135245997","https://openalex.org/W2150722677","https://openalex.org/W2162167806","https://openalex.org/W2165801966","https://openalex.org/W2171728525","https://openalex.org/W4229530126"],"related_works":["https://openalex.org/W4287880334","https://openalex.org/W3006513224","https://openalex.org/W4366700029","https://openalex.org/W2046456988","https://openalex.org/W4285230481","https://openalex.org/W2069592018","https://openalex.org/W2357409937","https://openalex.org/W2075740387","https://openalex.org/W4385769873","https://openalex.org/W4210897550"],"abstract_inverted_index":{"Multiple":[0],"model":[1,26,36,115],"estimation":[2,27,73,96,116],"is":[3,28],"an":[4,19],"important":[5,15],"problem":[6],"in":[7,18,24,103,134],"computer":[8],"vision.":[9],"Through":[10],"estimation,":[11],"one":[12],"can":[13],"detect":[14],"structural":[16],"information":[17],"image.":[20],"A":[21],"crucial":[22],"step":[23],"multiple":[25,114],"the":[29,47,63,78,84,87,104,125],"ability":[30,85,126],"to":[31,54,92,130],"dichotomize":[32],"inliers":[33],"of":[34,49,77,86,127],"a":[35,42,50],"from":[37],"outliers.":[38],"This":[39],"paper":[40],"proposes":[41],"novel":[43],"technique":[44],"for":[45,65,118],"estimating":[46],"scale":[48,57,72,89,95,111,133],"model.":[51],"In":[52],"contrast":[53],"previous":[55],"adaptive":[56],"estimate":[58,90,132],"works,":[59],"our":[60,110,128],"method":[61],"removes":[62],"need":[64],"user":[66],"provided":[67],"input.":[68],"We":[69],"achieve":[70],"accurate":[71,94],"through":[74],"consecutive":[75],"inspection":[76],"ordered":[79],"residuals.":[80],"Our":[81],"results":[82],"show":[83],"proposed":[88],"metric":[91],"maintain":[93],"even":[97],"with":[98,113],"over":[99],"90%":[100],"outliers":[101],"present":[102],"data.":[105],"Likewise,":[106],"we":[107],"also":[108],"apply":[109],"estimator":[112],"problems":[117],"detecting":[119],"planes":[120],"and":[121],"two-view":[122],"motions,":[123],"demonstrating":[124],"approach":[129],"accurately":[131],"real":[135],"application":[136],"oriented":[137],"scenarios.":[138]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
