{"id":"https://openalex.org/W2164535573","doi":"https://doi.org/10.1109/cvpr.2008.4587448","title":"Partitioning of image datasets using discriminative context information","display_name":"Partitioning of image datasets using discriminative context information","publication_year":2008,"publication_date":"2008-06-01","ids":{"openalex":"https://openalex.org/W2164535573","doi":"https://doi.org/10.1109/cvpr.2008.4587448","mag":"2164535573"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr.2008.4587448","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2008.4587448","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/A5068085751","display_name":"Christoph H. Lampert","orcid":"https://orcid.org/0000-0001-8622-7887"},"institutions":[{"id":"https://openalex.org/I4210112925","display_name":"Max Planck Institute for Biological Cybernetics","ror":"https://ror.org/026nmvv73","country_code":"DE","type":"facility","lineage":["https://openalex.org/I149899117","https://openalex.org/I4210112925"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Christoph H. Lampert","raw_affiliation_strings":["Max-Planck Institute of Biological Cybernetics, Tubingen, Germany"],"affiliations":[{"raw_affiliation_string":"Max-Planck Institute of Biological Cybernetics, Tubingen, Germany","institution_ids":["https://openalex.org/I4210112925"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5068085751"],"corresponding_institution_ids":["https://openalex.org/I4210112925"],"apc_list":null,"apc_paid":null,"fwci":0.355,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.68353562,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"14","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval 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/T10627","display_name":"Advanced Image and Video Retrieval 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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9958000183105469,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9940999746322632,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.7826346158981323},{"id":"https://openalex.org/keywords/mnist-database","display_name":"MNIST database","score":0.6834324598312378},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6787217855453491},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6641245484352112},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.6348853707313538},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6155022978782654},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5237076878547668},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5230175852775574},{"id":"https://openalex.org/keywords/disjoint-sets","display_name":"Disjoint sets","score":0.5050817131996155},{"id":"https://openalex.org/keywords/partition","display_name":"Partition (number theory)","score":0.487806111574173},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3522968888282776},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2583625316619873},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.10025396943092346}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7826346158981323},{"id":"https://openalex.org/C190502265","wikidata":"https://www.wikidata.org/wiki/Q17069496","display_name":"MNIST database","level":3,"score":0.6834324598312378},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6787217855453491},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6641245484352112},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.6348853707313538},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6155022978782654},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5237076878547668},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5230175852775574},{"id":"https://openalex.org/C45340560","wikidata":"https://www.wikidata.org/wiki/Q215382","display_name":"Disjoint sets","level":2,"score":0.5050817131996155},{"id":"https://openalex.org/C42812","wikidata":"https://www.wikidata.org/wiki/Q1082910","display_name":"Partition (number theory)","level":2,"score":0.487806111574173},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3522968888282776},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2583625316619873},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.10025396943092346},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","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}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1109/cvpr.2008.4587448","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2008.4587448","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"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.165.7869","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.165.7869","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.kyb.tuebingen.mpg.de/publications/attachments/CVPR2008-Lampert_5083%5B0%5D.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.332.3578","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.332.3578","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://eprints.pascal-network.org/archive/00004801/01/lampert-cvpr2008b.pdf","raw_type":"text"},{"id":"pmh:oai:edoc.mpg.de:420019","is_oa":false,"landing_page_url":"http://edoc.mpg.de/420019","pdf_url":null,"source":{"id":"https://openalex.org/S4406922265","display_name":"Max Planck Institute for Plasma Physics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2008), 1-8 (2008)","raw_type":"Conference-Paper"},{"id":"pmh:oai:pure.mpg.de:item_1789882","is_oa":false,"landing_page_url":"http://hdl.handle.net/11858/00-001M-0000-0013-C905-F","pdf_url":null,"source":{"id":"https://openalex.org/S4306400654","display_name":"MPG.PuRe (Max Planck Society)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I149899117","host_organization_name":"Max Planck Society","host_organization_lineage":["https://openalex.org/I149899117"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2008 IEEE Conference on Computer Vision and Pattern Recognition","raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7699999809265137,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W2283060","https://openalex.org/W92894758","https://openalex.org/W1494019289","https://openalex.org/W1526146785","https://openalex.org/W1540155273","https://openalex.org/W1576445103","https://openalex.org/W1943383135","https://openalex.org/W1971784203","https://openalex.org/W1990975153","https://openalex.org/W2022686119","https://openalex.org/W2050032036","https://openalex.org/W2095796212","https://openalex.org/W2115657355","https://openalex.org/W2121947440","https://openalex.org/W2127218421","https://openalex.org/W2132820034","https://openalex.org/W2147025064","https://openalex.org/W2147898188","https://openalex.org/W2148603752","https://openalex.org/W2150884987","https://openalex.org/W2162098863","https://openalex.org/W2164500538","https://openalex.org/W2165874743","https://openalex.org/W2319660501","https://openalex.org/W6600095579","https://openalex.org/W6603760306","https://openalex.org/W6631556622","https://openalex.org/W6633328910","https://openalex.org/W6634343353","https://openalex.org/W6677945368","https://openalex.org/W6678914141","https://openalex.org/W6679854563","https://openalex.org/W6684127227","https://openalex.org/W6684578312"],"related_works":["https://openalex.org/W2950475743","https://openalex.org/W4386603768","https://openalex.org/W2886711096","https://openalex.org/W4380078352","https://openalex.org/W3046591097","https://openalex.org/W2015634066","https://openalex.org/W2018845581","https://openalex.org/W2069654053","https://openalex.org/W3046629113","https://openalex.org/W2048339306"],"abstract_inverted_index":{"We":[0,119],"propose":[1],"a":[2,37,58,88,125,151,160],"new":[3],"method":[4],"to":[5,48,104],"partition":[6],"an":[7],"unlabeled":[8],"dataset,":[9],"called":[10],"Discriminative":[11],"Context":[12],"Partitioning":[13],"(DCP).":[14],"It":[15],"is":[16,45,93],"motivated":[17],"by":[18,61],"the":[19,23,30,69,79,87,96,105,108,113,131,141,154],"idea":[20],"of":[21,40,71,91,98,107,146,153],"splitting":[22],"dataset":[24,156],"based":[25,56,83],"only":[26],"on":[27,57,140,150],"how":[28,130],"well":[29],"resulting":[31,132],"parts":[32],"can":[33,135,164],"be":[34,136],"separated":[35],"from":[36],"context":[38],"class":[39],"disjoint":[41],"data":[42],"points.":[43],"This":[44],"in":[46,68,76,102,169],"contrast":[47],"typical":[49],"clustering":[50,173],"techniques":[51,174],"like":[52],"K-means":[53],"that":[54,81],"are":[55,116],"generative":[59],"model":[60],"implicitly":[62],"or":[63,111],"explicitly":[64],"searching":[65],"for":[66],"modes":[67],"distribution":[70],"samples.":[72],"The":[73],"discriminative":[74],"criterion":[75],"DCP":[77,163],"avoids":[78],"problems":[80],"density":[82],"methods":[84],"have":[85],"when":[86,95],"priori":[89],"assumption":[90],"multimodality":[92],"violated,":[94],"number":[97],"samples":[99],"becomes":[100],"small":[101],"relation":[103],"dimensionality":[106],"feature":[109],"space,":[110],"if":[112],"cluster":[114],"sizes":[115],"strongly":[117],"unbalanced.":[118],"formulate":[120],"DCPpsilas":[121],"separation":[122],"property":[123],"as":[124],"large-margin":[126],"criterion,":[127],"and":[128,143,149],"show":[129,157],"optimization":[133],"problem":[134],"solved":[137],"efficiently.":[138],"Experiments":[139],"MNIST":[142],"USPS":[144],"datasets":[145],"handwritten":[147],"digits":[148],"subset":[152],"Caltech256":[155],"that,":[158],"given":[159],"suitable":[161],"context,":[162],"achieve":[165],"good":[166],"results":[167],"even":[168],"situation":[170],"where":[171],"density-based":[172],"fail.":[175]},"counts_by_year":[{"year":2012,"cited_by_count":1}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}