{"id":"https://openalex.org/W2120287764","doi":"https://doi.org/10.1109/tgrs.2011.2171691","title":"Mixture Model for Multiple Instance Regression and Applications in Remote Sensing","display_name":"Mixture Model for Multiple Instance Regression and Applications in Remote Sensing","publication_year":2011,"publication_date":"2011-12-02","ids":{"openalex":"https://openalex.org/W2120287764","doi":"https://doi.org/10.1109/tgrs.2011.2171691","mag":"2120287764"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2011.2171691","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2011.2171691","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Geoscience and Remote Sensing","raw_type":"journal-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/A5100697511","display_name":"Zhuang Wang","orcid":"https://orcid.org/0000-0002-7895-4416"},"institutions":[{"id":"https://openalex.org/I4210137693","display_name":"Siemens (United States)","ror":"https://ror.org/04axb7e79","country_code":"US","type":"company","lineage":["https://openalex.org/I1325886976","https://openalex.org/I4210137693"]},{"id":"https://openalex.org/I84392919","display_name":"Temple University","ror":"https://ror.org/00kx1jb78","country_code":"US","type":"education","lineage":["https://openalex.org/I84392919"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Zhuang Wang","raw_affiliation_strings":["Department of Computer and Information Science, Temple University, Philadelphia, PA, USA","Siemens AG Corporate Research and Development, Princeton, NJ, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer and Information Science, Temple University, Philadelphia, PA, USA","institution_ids":["https://openalex.org/I84392919"]},{"raw_affiliation_string":"Siemens AG Corporate Research and Development, Princeton, NJ, USA","institution_ids":["https://openalex.org/I4210137693"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069308334","display_name":"Liang Lan","orcid":"https://orcid.org/0000-0002-0427-977X"},"institutions":[{"id":"https://openalex.org/I84392919","display_name":"Temple University","ror":"https://ror.org/00kx1jb78","country_code":"US","type":"education","lineage":["https://openalex.org/I84392919"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Liang Lan","raw_affiliation_strings":["Department of Computer and Information Science, Temple University, Philadelphia, PA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer and Information Science, Temple University, Philadelphia, PA, USA","institution_ids":["https://openalex.org/I84392919"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5059847153","display_name":"Slobodan Vu\u010deti\u0107","orcid":"https://orcid.org/0000-0001-5884-6293"},"institutions":[{"id":"https://openalex.org/I84392919","display_name":"Temple University","ror":"https://ror.org/00kx1jb78","country_code":"US","type":"education","lineage":["https://openalex.org/I84392919"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Slobodan Vucetic","raw_affiliation_strings":["Department of Computer and Information Science, Temple University, Philadelphia, PA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer and Information Science, Temple University, Philadelphia, PA, USA","institution_ids":["https://openalex.org/I84392919"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100697511"],"corresponding_institution_ids":["https://openalex.org/I4210137693","https://openalex.org/I84392919"],"apc_list":null,"apc_paid":null,"fwci":1.5338,"has_fulltext":false,"cited_by_count":43,"citation_normalized_percentile":{"value":0.86031672,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"50","issue":"6","first_page":"2226","last_page":"2237"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9961000084877014,"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"}},"topics":[{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9961000084877014,"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"}},{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.989799976348877,"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/T10111","display_name":"Remote Sensing in Agriculture","score":0.9728000164031982,"subfield":{"id":"https://openalex.org/subfields/2303","display_name":"Ecology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7212023735046387},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.6184404492378235},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.5465878248214722},{"id":"https://openalex.org/keywords/expectation\u2013maximization-algorithm","display_name":"Expectation\u2013maximization algorithm","score":0.5077546834945679},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.48754996061325073},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4752238392829895},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.46876758337020874},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.4668980538845062},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.4363422095775604},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43606123328208923},{"id":"https://openalex.org/keywords/statistical-model","display_name":"Statistical model","score":0.42277994751930237},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3466927409172058},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.33874762058258057},{"id":"https://openalex.org/keywords/maximum-likelihood","display_name":"Maximum likelihood","score":0.2312624156475067},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14361104369163513},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.0902506411075592},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.07929503917694092}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7212023735046387},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.6184404492378235},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.5465878248214722},{"id":"https://openalex.org/C182081679","wikidata":"https://www.wikidata.org/wiki/Q1275153","display_name":"Expectation\u2013maximization algorithm","level":3,"score":0.5077546834945679},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.48754996061325073},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4752238392829895},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.46876758337020874},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.4668980538845062},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.4363422095775604},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43606123328208923},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.42277994751930237},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3466927409172058},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33874762058258057},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.2312624156475067},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14361104369163513},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0902506411075592},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.07929503917694092},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2011.2171691","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2011.2171691","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Geoscience and Remote Sensing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W181444816","https://openalex.org/W842265099","https://openalex.org/W1540386283","https://openalex.org/W1550821944","https://openalex.org/W1554039773","https://openalex.org/W1988115337","https://openalex.org/W2009821028","https://openalex.org/W2031528200","https://openalex.org/W2048801813","https://openalex.org/W2049633694","https://openalex.org/W2055267538","https://openalex.org/W2057553587","https://openalex.org/W2076291476","https://openalex.org/W2089433206","https://openalex.org/W2093623508","https://openalex.org/W2105353986","https://openalex.org/W2108745803","https://openalex.org/W2110119381","https://openalex.org/W2115049406","https://openalex.org/W2118697091","https://openalex.org/W2119567876","https://openalex.org/W2125070195","https://openalex.org/W2136595724","https://openalex.org/W2143908786","https://openalex.org/W2145458969","https://openalex.org/W2152195571","https://openalex.org/W2154318594","https://openalex.org/W2158801725","https://openalex.org/W2162685317","https://openalex.org/W2169678197","https://openalex.org/W2170041334","https://openalex.org/W2510024936","https://openalex.org/W3129711340","https://openalex.org/W4244946557","https://openalex.org/W6623418179","https://openalex.org/W6632200337","https://openalex.org/W6633085109","https://openalex.org/W6676245398","https://openalex.org/W6677574362","https://openalex.org/W6680240620","https://openalex.org/W6683033130","https://openalex.org/W6725650603"],"related_works":["https://openalex.org/W2473373438","https://openalex.org/W2368486525","https://openalex.org/W2077224612","https://openalex.org/W84255947","https://openalex.org/W2153481672","https://openalex.org/W4312864369","https://openalex.org/W2014842417","https://openalex.org/W2891133681","https://openalex.org/W2061347451","https://openalex.org/W1505865477"],"abstract_inverted_index":{"The":[0,27,103,123,142],"multiple":[1,20],"instance":[2,82],"regression":[3,33],"(MIR)":[4],"problem":[5],"arises":[6],"when":[7],"a":[8,12,32,56,67,80],"data":[9,130,134],"set":[10],"is":[11,29,71,84,93,108],"collection":[13],"of":[14,40,99,157],"bags,":[15],"where":[16],"each":[17,77],"bag":[18,64,78,88],"contains":[19,79],"instances":[21],"sharing":[22],"the":[23,87,97,100,146,154,158],"identical":[24],"real-valued":[25],"label.":[26,89],"goal":[28],"to":[30,95],"train":[31],"model":[34,105],"that":[35,62,76,145],"can":[36,48,116],"accurately":[37],"predict":[38],"label":[39],"an":[41,74],"unlabeled":[42],"bag.":[43],"Many":[44],"remote":[45,132],"sensing":[46,133],"applications":[47],"be":[49,117],"studied":[50],"within":[51],"this":[52],"setting.":[53],"We":[54],"propose":[55],"novel":[57],"probabilistic":[58],"framework":[59,107],"for":[60,86,135],"MIR":[61,106,114,148],"represents":[63],"labels":[65],"with":[66],"mixture":[68,101,104],"model.":[69,102],"It":[70],"based":[72],"on":[73,128],"assumption":[75],"prime":[81],"which":[83],"responsible":[85],"An":[90],"expectation-maximization":[91],"algorithm":[92],"proposed":[94,124,147],"maximize":[96],"likelihood":[98],"quite":[109],"flexible,":[110],"and":[111,131,138],"several":[112],"existing":[113],"algorithms":[115,125,149],"described":[118],"as":[119],"its":[120],"special":[121],"cases.":[122],"were":[126],"evaluated":[127],"synthetic":[129],"aerosol":[136],"retrieval":[137],"crop":[139],"yield":[140],"prediction.":[141],"results":[143],"show":[144],"achieve":[150],"higher":[151],"accuracy":[152],"than":[153],"previous":[155],"state":[156],"art.":[159]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2023,"cited_by_count":3},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":7},{"year":2017,"cited_by_count":6},{"year":2016,"cited_by_count":7},{"year":2014,"cited_by_count":2},{"year":2013,"cited_by_count":1}],"updated_date":"2026-03-10T16:38:18.471706","created_date":"2025-10-10T00:00:00"}