{"id":"https://openalex.org/W2136990691","doi":"https://doi.org/10.1109/igarss.2002.1026711","title":"Multiband SAR classification using contextual analysis: annealing segmentation vs. a neural kernel-based approach","display_name":"Multiband SAR classification using contextual analysis: annealing segmentation vs. a neural kernel-based approach","publication_year":2003,"publication_date":"2003-10-01","ids":{"openalex":"https://openalex.org/W2136990691","doi":"https://doi.org/10.1109/igarss.2002.1026711","mag":"2136990691"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2002.1026711","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2002.1026711","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE International Geoscience and Remote Sensing Symposium","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/A5071889277","display_name":"T.M. Pellizzeri","orcid":null},"institutions":[{"id":"https://openalex.org/I861853513","display_name":"Sapienza University of Rome","ror":"https://ror.org/02be6w209","country_code":"IT","type":"education","lineage":["https://openalex.org/I861853513"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"T. Macri Pellizzeri","raw_affiliation_strings":["INFOCOM Dpt, University of Roma La Sapienza, Italy","INFOCOM Department, University of Rome \u00bfLa Sapienza\u00bf, Italy"],"affiliations":[{"raw_affiliation_string":"INFOCOM Dpt, University of Roma La Sapienza, Italy","institution_ids":["https://openalex.org/I861853513"]},{"raw_affiliation_string":"INFOCOM Department, University of Rome \u00bfLa Sapienza\u00bf, Italy","institution_ids":["https://openalex.org/I861853513"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066694835","display_name":"Fabio Dell\u2019Acqua","orcid":"https://orcid.org/0000-0002-0044-2998"},"institutions":[{"id":"https://openalex.org/I861853513","display_name":"Sapienza University of Rome","ror":"https://ror.org/02be6w209","country_code":"IT","type":"education","lineage":["https://openalex.org/I861853513"]},{"id":"https://openalex.org/I25217355","display_name":"University of Pavia","ror":"https://ror.org/00s6t1f81","country_code":"IT","type":"education","lineage":["https://openalex.org/I25217355"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"F. Dell'Acqua","raw_affiliation_strings":["Department of Electronics, University of Pavia, Italy","University of Rome \u201cLa Sapienza \u201d"],"affiliations":[{"raw_affiliation_string":"Department of Electronics, University of Pavia, Italy","institution_ids":["https://openalex.org/I25217355"]},{"raw_affiliation_string":"University of Rome \u201cLa Sapienza \u201d","institution_ids":["https://openalex.org/I861853513"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006623289","display_name":"Paolo Gamba","orcid":"https://orcid.org/0000-0002-9576-6337"},"institutions":[{"id":"https://openalex.org/I25217355","display_name":"University of Pavia","ror":"https://ror.org/00s6t1f81","country_code":"IT","type":"education","lineage":["https://openalex.org/I25217355"]},{"id":"https://openalex.org/I861853513","display_name":"Sapienza University of Rome","ror":"https://ror.org/02be6w209","country_code":"IT","type":"education","lineage":["https://openalex.org/I861853513"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"P. Gamba","raw_affiliation_strings":["Department of Electronics, University of Pavia, Italy","University of Rome \u201cLa Sapienza \u201d"],"affiliations":[{"raw_affiliation_string":"Department of Electronics, University of Pavia, Italy","institution_ids":["https://openalex.org/I25217355"]},{"raw_affiliation_string":"University of Rome \u201cLa Sapienza \u201d","institution_ids":["https://openalex.org/I861853513"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049188669","display_name":"P. Lombardo","orcid":"https://orcid.org/0000-0001-5018-5048"},"institutions":[{"id":"https://openalex.org/I861853513","display_name":"Sapienza University of Rome","ror":"https://ror.org/02be6w209","country_code":"IT","type":"education","lineage":["https://openalex.org/I861853513"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"P. Lombardo","raw_affiliation_strings":["INFOCOM Dpt, University of Roma La Sapienza, Italy","Engineering, Electronics and Telecommunications"],"affiliations":[{"raw_affiliation_string":"INFOCOM Dpt, University of Roma La Sapienza, Italy","institution_ids":["https://openalex.org/I861853513"]},{"raw_affiliation_string":"Engineering, Electronics and Telecommunications","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086090264","display_name":"D. Mazzola","orcid":null},"institutions":[{"id":"https://openalex.org/I861853513","display_name":"Sapienza University of Rome","ror":"https://ror.org/02be6w209","country_code":"IT","type":"education","lineage":["https://openalex.org/I861853513"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"D. Mazzola","raw_affiliation_strings":["INFOCOM Dpt, University of Roma La Sapienza, Italy","University of Rome \u201cLa Sapienza \u201d"],"affiliations":[{"raw_affiliation_string":"INFOCOM Dpt, University of Roma La Sapienza, Italy","institution_ids":["https://openalex.org/I861853513"]},{"raw_affiliation_string":"University of Rome \u201cLa Sapienza \u201d","institution_ids":["https://openalex.org/I861853513"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5071889277"],"corresponding_institution_ids":["https://openalex.org/I861853513"],"apc_list":null,"apc_paid":null,"fwci":0.2759,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.59796278,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"5","issue":null,"first_page":"2593","last_page":"2595"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12316","display_name":"Oil Spill Detection and Mitigation","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/2310","display_name":"Pollution"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12316","display_name":"Oil Spill Detection and Mitigation","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/2310","display_name":"Pollution"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10995","display_name":"Methane Hydrates and Related Phenomena","score":0.9939000010490417,"subfield":{"id":"https://openalex.org/subfields/2304","display_name":"Environmental Chemistry"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9907000064849854,"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/computer-science","display_name":"Computer science","score":0.7410709261894226},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.6574793457984924},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6027728319168091},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5949944257736206},{"id":"https://openalex.org/keywords/simulated-annealing","display_name":"Simulated annealing","score":0.5700221061706543},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5664968490600586},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.5515093207359314},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5338256359100342},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.48195144534111023},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4549131691455841},{"id":"https://openalex.org/keywords/synthetic-aperture-radar","display_name":"Synthetic aperture radar","score":0.45028620958328247},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.44724032282829285},{"id":"https://openalex.org/keywords/homogeneous","display_name":"Homogeneous","score":0.4462147355079651},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.4325944483280182},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.33349156379699707},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.32965490221977234},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2649948000907898},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1299516260623932}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7410709261894226},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.6574793457984924},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6027728319168091},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5949944257736206},{"id":"https://openalex.org/C126980161","wikidata":"https://www.wikidata.org/wiki/Q863783","display_name":"Simulated annealing","level":2,"score":0.5700221061706543},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5664968490600586},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.5515093207359314},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5338256359100342},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.48195144534111023},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4549131691455841},{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.45028620958328247},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.44724032282829285},{"id":"https://openalex.org/C66882249","wikidata":"https://www.wikidata.org/wiki/Q169336","display_name":"Homogeneous","level":2,"score":0.4462147355079651},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.4325944483280182},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33349156379699707},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32965490221977234},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2649948000907898},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1299516260623932},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/igarss.2002.1026711","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2002.1026711","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"},{"id":"pmh:oai:iris.uniroma1.it:11573/425373","is_oa":false,"landing_page_url":"http://hdl.handle.net/11573/425373","pdf_url":null,"source":{"id":"https://openalex.org/S4377196107","display_name":"IRIS Research product catalog (Sapienza University of Rome)","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":"","raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.8500000238418579,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":6,"referenced_works":["https://openalex.org/W2054116266","https://openalex.org/W2054423382","https://openalex.org/W2076210377","https://openalex.org/W2320961246","https://openalex.org/W4244628856","https://openalex.org/W6700306401"],"related_works":["https://openalex.org/W2025427163","https://openalex.org/W2392013129","https://openalex.org/W2113777112","https://openalex.org/W2884994975","https://openalex.org/W2357727223","https://openalex.org/W2067147118","https://openalex.org/W2153172467","https://openalex.org/W4210966920","https://openalex.org/W2550009779","https://openalex.org/W2599254681"],"abstract_inverted_index":{"In":[0],"this":[1],"paper":[2],"we":[3],"derive":[4],"two":[5,102],"techniques":[6,25,49,103],"for":[7],"the":[8,32,36,61,87,97,101,113],"classification":[9],"of":[10,31,35,74,78,89,96],"multipolarimetric/multifrequency":[11,75],"SAR":[12],"images,":[13],"based":[14],"respectively":[15],"on":[16,20],"a":[17,21,72,79,108],"statistical":[18,114],"and":[19,65],"neural":[22],"approach.":[23],"Both":[24],"are":[26,50,69],"especially":[27],"designed":[28],"to":[29,56,71,82,117],"exploit":[30],"spatial":[33],"structure":[34],"observed":[37],"scene,":[38],"thus":[39],"identifying":[40],"homogeneous":[41],"regions":[42],"that":[43],"can":[44],"be":[45],"jointly":[46],"classified.":[47],"Such":[48],"useful":[51],"when":[52],"looking":[53],"at":[54],"medium":[55],"large":[57],"scale":[58],"features,":[59],"like":[60],"boundaries":[62],"between":[63],"urban":[64,80],"non-urban":[66],"areas.":[67,92],"They":[68],"applied":[70],"set":[73],"SIRC":[76],"images":[77],"area,":[81],"test":[83],"their":[84],"effectiveness":[85],"in":[86],"identification":[88],"built":[90],"up":[91],"A":[93],"quantitative":[94],"comparison":[95],"results":[98],"achievable":[99],"with":[100],"is":[104],"carried":[105],"out,":[106],"showing":[107],"similar":[109],"behavior,":[110],"even":[111],"if":[112],"approach":[115],"tends":[116],"achieve":[118],"better":[119],"performance.":[120]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}