{"id":"https://openalex.org/W2039091194","doi":"https://doi.org/10.1109/icip.2011.6115784","title":"SAR image classification with non-stationary Multinomial Logistic mixture of amplitude and texture densities","display_name":"SAR image classification with non-stationary Multinomial Logistic mixture of amplitude and texture densities","publication_year":2011,"publication_date":"2011-09-01","ids":{"openalex":"https://openalex.org/W2039091194","doi":"https://doi.org/10.1109/icip.2011.6115784","mag":"2039091194"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2011.6115784","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2011.6115784","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 18th IEEE International Conference on Image Processing","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://ir.cwi.nl/pub/18709","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5054230085","display_name":"Koray Kayabol","orcid":"https://orcid.org/0000-0003-0053-2800"},"institutions":[{"id":"https://openalex.org/I1326498283","display_name":"Institut national de recherche en sciences et technologies du num\u00e9rique","ror":"https://ror.org/02kvxyf05","country_code":"FR","type":"government","lineage":["https://openalex.org/I1326498283"]},{"id":"https://openalex.org/I4210106545","display_name":"Centre Inria d'Universit\u00e9 C\u00f4te d'Azur","ror":"https://ror.org/01nzkaw91","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1326498283","https://openalex.org/I201841394","https://openalex.org/I4210106545"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Koray Kayabol","raw_affiliation_strings":["Ariana, INRIA Sophia Antipolis Mediterranee, Sophia-Antipolis, France","Ariana, INRIA Sophia Antipolis Mediterranee, 2004 route des Lucioles, BP93, 06902 Sophia Antipolis Cedex, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ariana, INRIA Sophia Antipolis Mediterranee, Sophia-Antipolis, France","institution_ids":["https://openalex.org/I1326498283","https://openalex.org/I4210106545"]},{"raw_affiliation_string":"Ariana, INRIA Sophia Antipolis Mediterranee, 2004 route des Lucioles, BP93, 06902 Sophia Antipolis Cedex, France","institution_ids":["https://openalex.org/I1326498283"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103414170","display_name":"Aur\u00e9lie Voisin","orcid":null},"institutions":[{"id":"https://openalex.org/I1326498283","display_name":"Institut national de recherche en sciences et technologies du num\u00e9rique","ror":"https://ror.org/02kvxyf05","country_code":"FR","type":"government","lineage":["https://openalex.org/I1326498283"]},{"id":"https://openalex.org/I4210106545","display_name":"Centre Inria d'Universit\u00e9 C\u00f4te d'Azur","ror":"https://ror.org/01nzkaw91","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1326498283","https://openalex.org/I201841394","https://openalex.org/I4210106545"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Aurelie Voisin","raw_affiliation_strings":["Ariana, INRIA Sophia Antipolis Mediterranee, Sophia-Antipolis, France","Ariana, INRIA Sophia Antipolis Mediterranee, 2004 route des Lucioles, BP93, 06902 Sophia Antipolis Cedex, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ariana, INRIA Sophia Antipolis Mediterranee, Sophia-Antipolis, France","institution_ids":["https://openalex.org/I1326498283","https://openalex.org/I4210106545"]},{"raw_affiliation_string":"Ariana, INRIA Sophia Antipolis Mediterranee, 2004 route des Lucioles, BP93, 06902 Sophia Antipolis Cedex, France","institution_ids":["https://openalex.org/I1326498283"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018158883","display_name":"Josiane Zerubia","orcid":"https://orcid.org/0000-0002-7444-0856"},"institutions":[{"id":"https://openalex.org/I1326498283","display_name":"Institut national de recherche en sciences et technologies du num\u00e9rique","ror":"https://ror.org/02kvxyf05","country_code":"FR","type":"government","lineage":["https://openalex.org/I1326498283"]},{"id":"https://openalex.org/I4210106545","display_name":"Centre Inria d'Universit\u00e9 C\u00f4te d'Azur","ror":"https://ror.org/01nzkaw91","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1326498283","https://openalex.org/I201841394","https://openalex.org/I4210106545"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Josiane Zerubia","raw_affiliation_strings":["Ariana, INRIA Sophia Antipolis Mediterranee, Sophia-Antipolis, France","Ariana, INRIA Sophia Antipolis Mediterranee, 2004 route des Lucioles, BP93, 06902 Sophia Antipolis Cedex, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ariana, INRIA Sophia Antipolis Mediterranee, Sophia-Antipolis, France","institution_ids":["https://openalex.org/I1326498283","https://openalex.org/I4210106545"]},{"raw_affiliation_string":"Ariana, INRIA Sophia Antipolis Mediterranee, 2004 route des Lucioles, BP93, 06902 Sophia Antipolis Cedex, France","institution_ids":["https://openalex.org/I1326498283"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"10","issue":null,"first_page":"169","last_page":"172"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9927999973297119,"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":0.9927999973297119,"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/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9884999990463257,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9869999885559082,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/synthetic-aperture-radar","display_name":"Synthetic aperture radar","score":0.7594824433326721},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7158253192901611},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6871711611747742},{"id":"https://openalex.org/keywords/multinomial-logistic-regression","display_name":"Multinomial logistic regression","score":0.6700221300125122},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.6095409393310547},{"id":"https://openalex.org/keywords/markov-random-field","display_name":"Markov random field","score":0.599504828453064},{"id":"https://openalex.org/keywords/expectation\u2013maximization-algorithm","display_name":"Expectation\u2013maximization algorithm","score":0.5790596604347229},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5397838354110718},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.5355315804481506},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.4366075098514557},{"id":"https://openalex.org/keywords/radar-imaging","display_name":"Radar imaging","score":0.41361454129219055},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.41080382466316223},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.3676597476005554},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3652583360671997},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.29546335339546204},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.24797731637954712},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.24643683433532715},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.22933053970336914},{"id":"https://openalex.org/keywords/maximum-likelihood","display_name":"Maximum likelihood","score":0.14552992582321167}],"concepts":[{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.7594824433326721},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7158253192901611},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6871711611747742},{"id":"https://openalex.org/C117568660","wikidata":"https://www.wikidata.org/wiki/Q1650843","display_name":"Multinomial logistic regression","level":2,"score":0.6700221300125122},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.6095409393310547},{"id":"https://openalex.org/C2778045648","wikidata":"https://www.wikidata.org/wiki/Q176827","display_name":"Markov random field","level":4,"score":0.599504828453064},{"id":"https://openalex.org/C182081679","wikidata":"https://www.wikidata.org/wiki/Q1275153","display_name":"Expectation\u2013maximization algorithm","level":3,"score":0.5790596604347229},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5397838354110718},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.5355315804481506},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.4366075098514557},{"id":"https://openalex.org/C10929652","wikidata":"https://www.wikidata.org/wiki/Q7279985","display_name":"Radar imaging","level":3,"score":0.41361454129219055},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.41080382466316223},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.3676597476005554},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3652583360671997},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.29546335339546204},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.24797731637954712},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.24643683433532715},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.22933053970336914},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.14552992582321167},{"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/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/icip.2011.6115784","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2011.6115784","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 18th IEEE International Conference on Image Processing","raw_type":"proceedings-article"},{"id":"pmh:cwi:oai:cwi.nl:18709","is_oa":true,"landing_page_url":"https://ir.cwi.nl/pub/18709","pdf_url":null,"source":{"id":"https://openalex.org/S4306401843","display_name":"Data Archiving and Networked Services (DANS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1322597698","host_organization_name":"Royal Netherlands Academy of Arts and Sciences","host_organization_lineage":["https://openalex.org/I1322597698"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/conferencepaper"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.651.8726","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.651.8726","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"https://hal.inria.fr/inria-00592252/document/","raw_type":"text"},{"id":"pmh:oai:HAL:inria-00592252v1","is_oa":true,"landing_page_url":"https://inria.hal.science/inria-00592252","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE International Conference on Image Processing ICIP, Sep 2011, Brussels, Belgium. pp.173-176","raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":{"id":"pmh:cwi:oai:cwi.nl:18709","is_oa":true,"landing_page_url":"https://ir.cwi.nl/pub/18709","pdf_url":null,"source":{"id":"https://openalex.org/S4306401843","display_name":"Data Archiving and Networked Services (DANS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1322597698","host_organization_name":"Royal Netherlands Academy of Arts and Sciences","host_organization_lineage":["https://openalex.org/I1322597698"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/conferencepaper"},"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.8500000238418579,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320313934","display_name":"Institut national de recherche en informatique et en automatique (INRIA)","ror":"https://ror.org/02kvxyf05"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1602107991","https://openalex.org/W1964262399","https://openalex.org/W1987517448","https://openalex.org/W1990420575","https://openalex.org/W1997063559","https://openalex.org/W2008499060","https://openalex.org/W2020999234","https://openalex.org/W2044465660","https://openalex.org/W2049549449","https://openalex.org/W2059279601","https://openalex.org/W2079182758","https://openalex.org/W2109394460","https://openalex.org/W2120336501","https://openalex.org/W2132106992","https://openalex.org/W2150579376","https://openalex.org/W2158275940","https://openalex.org/W3098814547","https://openalex.org/W6670322988"],"related_works":["https://openalex.org/W2473373438","https://openalex.org/W2368486525","https://openalex.org/W2077224612","https://openalex.org/W2153481672","https://openalex.org/W2153238387","https://openalex.org/W84255947","https://openalex.org/W4312864369","https://openalex.org/W2014842417","https://openalex.org/W2891133681","https://openalex.org/W2061347451"],"abstract_inverted_index":{"We":[0,23,73,89],"combine":[1],"both":[2,101],"amplitude":[3],"and":[4,85,97,103],"texture":[5,47],"statistics":[6],"of":[7,16,36,94],"the":[8,29,34,37,75,82,87],"Synthetic":[9],"Aperture":[10],"Radar":[11],"(SAR)":[12],"images":[13],"using":[14],"Products":[15],"Experts":[17],"(PoE)":[18],"approach":[19],"for":[20],"classification":[21,92],"purpose.":[22],"use":[24],"Nak-agami":[25],"density":[26,66],"to":[27,67,80],"model":[28,33,48,60],"class":[30,58,71,83],"amplitudes.":[31],"To":[32],"textures":[35],"classes,":[38],"we":[39],"exploit":[40],"a":[41,64],"non-Gaussian":[42],"Markov":[43],"Random":[44],"Field":[45],"(MRF)":[46],"with":[49],"t-distributed":[50],"regression":[51],"error.":[52],"Non-stationary":[53],"Multinomial":[54],"Logistic":[55],"(MnL)":[56],"latent":[57],"label":[59],"is":[61],"used":[62],"as":[63],"mixture":[65],"obtain":[68],"spatially":[69],"smooth":[70],"segments.":[72],"perform":[74],"Classification":[76],"Expectation-Maximization":[77],"(CEM)":[78],"algorithm":[79],"estimate":[81],"parameters":[84],"classify":[86],"pixels.":[88],"obtained":[90],"some":[91],"results":[93],"water,":[95],"land":[96],"urban":[98],"areas":[99],"in":[100],"supervised":[102],"semi-supervised":[104],"cases":[105],"on":[106],"TerraSAR-X":[107],"data.":[108]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":2},{"year":2013,"cited_by_count":2},{"year":2012,"cited_by_count":4}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}
