{"id":"https://openalex.org/W2015830361","doi":"https://doi.org/10.1002/(sici)1098-1098(199622)7:2<141::aid-ima11>3.0.co;2-4","title":"Remote sensing image segmentation using a Kalman filter-trained neural network","display_name":"Remote sensing image segmentation using a Kalman filter-trained neural network","publication_year":1996,"publication_date":"1996-01-01","ids":{"openalex":"https://openalex.org/W2015830361","doi":"https://doi.org/10.1002/(sici)1098-1098(199622)7:2<141::aid-ima11>3.0.co;2-4","mag":"2015830361"},"language":"en","primary_location":{"id":"doi:10.1002/(sici)1098-1098(199622)7:2<141::aid-ima11>3.0.co;2-4","is_oa":false,"landing_page_url":"https://doi.org/10.1002/(sici)1098-1098(199622)7:2<141::aid-ima11>3.0.co;2-4","pdf_url":null,"source":{"id":"https://openalex.org/S15952048","display_name":"International Journal of Imaging Systems and Technology","issn_l":"0899-9457","issn":["0899-9457","1098-1098"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Imaging Systems and Technology","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/A5110203335","display_name":"K.S. Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I22265921","display_name":"National Central University","ror":"https://ror.org/00944ve71","country_code":"TW","type":"education","lineage":["https://openalex.org/I22265921"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"K. S. Chen","raw_affiliation_strings":["Center for Space and Remote Sensing Research, National Central University, Chung-Li, Taiwan"],"affiliations":[{"raw_affiliation_string":"Center for Space and Remote Sensing Research, National Central University, Chung-Li, Taiwan","institution_ids":["https://openalex.org/I22265921"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111659899","display_name":"D.H. Tsay","orcid":null},"institutions":[{"id":"https://openalex.org/I22265921","display_name":"National Central University","ror":"https://ror.org/00944ve71","country_code":"TW","type":"education","lineage":["https://openalex.org/I22265921"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"D. H. Tsay","raw_affiliation_strings":["Center for Space and Remote Sensing Research, National Central University, Chung-Li, Taiwan"],"affiliations":[{"raw_affiliation_string":"Center for Space and Remote Sensing Research, National Central University, Chung-Li, Taiwan","institution_ids":["https://openalex.org/I22265921"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101651674","display_name":"Wei Huang","orcid":"https://orcid.org/0000-0003-1696-1503"},"institutions":[{"id":"https://openalex.org/I22265921","display_name":"National Central University","ror":"https://ror.org/00944ve71","country_code":"TW","type":"education","lineage":["https://openalex.org/I22265921"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"W. P. Huang","raw_affiliation_strings":["Center for Space and Remote Sensing Research, National Central University, Chung-Li, Taiwan"],"affiliations":[{"raw_affiliation_string":"Center for Space and Remote Sensing Research, National Central University, Chung-Li, Taiwan","institution_ids":["https://openalex.org/I22265921"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5048140408","display_name":"Y. C. Tzeng","orcid":null},"institutions":[{"id":"https://openalex.org/I22265921","display_name":"National Central University","ror":"https://ror.org/00944ve71","country_code":"TW","type":"education","lineage":["https://openalex.org/I22265921"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Y. C. Tzeng","raw_affiliation_strings":["Center for Space and Remote Sensing Research, National Central University, Chung-Li, Taiwan"],"affiliations":[{"raw_affiliation_string":"Center for Space and Remote Sensing Research, National Central University, Chung-Li, Taiwan","institution_ids":["https://openalex.org/I22265921"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5110203335"],"corresponding_institution_ids":["https://openalex.org/I22265921"],"apc_list":{"value":3450,"currency":"USD","value_usd":3450},"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.23560876,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"7","issue":"2","first_page":"141","last_page":"148"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9979000091552734,"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":0.9979000091552734,"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/T10801","display_name":"Synthetic Aperture Radar (SAR) Applications and Techniques","score":0.9973000288009644,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"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/T11698","display_name":"Underwater Acoustics Research","score":0.993399977684021,"subfield":{"id":"https://openalex.org/subfields/1910","display_name":"Oceanography"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7591387033462524},{"id":"https://openalex.org/keywords/kalman-filter","display_name":"Kalman filter","score":0.660500705242157},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6428409218788147},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6160914301872253},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5564975142478943},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.5332605242729187},{"id":"https://openalex.org/keywords/backpropagation","display_name":"Backpropagation","score":0.5133777856826782},{"id":"https://openalex.org/keywords/multilayer-perceptron","display_name":"Multilayer perceptron","score":0.49888157844543457},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.47892484068870544},{"id":"https://openalex.org/keywords/multispectral-image","display_name":"Multispectral image","score":0.4534074366092682},{"id":"https://openalex.org/keywords/extended-kalman-filter","display_name":"Extended Kalman filter","score":0.4367280900478363},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.33915936946868896}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7591387033462524},{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.660500705242157},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6428409218788147},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6160914301872253},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5564975142478943},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.5332605242729187},{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.5133777856826782},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.49888157844543457},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.47892484068870544},{"id":"https://openalex.org/C173163844","wikidata":"https://www.wikidata.org/wiki/Q1761440","display_name":"Multispectral image","level":2,"score":0.4534074366092682},{"id":"https://openalex.org/C206833254","wikidata":"https://www.wikidata.org/wiki/Q5421817","display_name":"Extended Kalman filter","level":3,"score":0.4367280900478363},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.33915936946868896}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1002/(sici)1098-1098(199622)7:2<141::aid-ima11>3.0.co;2-4","is_oa":false,"landing_page_url":"https://doi.org/10.1002/(sici)1098-1098(199622)7:2<141::aid-ima11>3.0.co;2-4","pdf_url":null,"source":{"id":"https://openalex.org/S15952048","display_name":"International Journal of Imaging Systems and Technology","issn_l":"0899-9457","issn":["0899-9457","1098-1098"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Imaging Systems and Technology","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.6800000071525574,"display_name":"Reduced inequalities"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321040","display_name":"National Science Council","ror":"https://ror.org/02kv4zf79"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W1918707195","https://openalex.org/W2555356437","https://openalex.org/W2417891382","https://openalex.org/W2076543106","https://openalex.org/W2523437662","https://openalex.org/W89844371","https://openalex.org/W2019891950","https://openalex.org/W2083196709","https://openalex.org/W2600618515","https://openalex.org/W4285523177"],"abstract_inverted_index":{"This":[0],"article":[1],"describes":[2],"the":[3,10,27,38,46,53,61,72,78,86,103,113,121,147,150,159,165],"application":[4],"of":[5,12,16,26,45,63,74,149,158,167],"a":[6,30,49,64,108],"neural":[7,90,105,162],"network":[8,28,47,82,106,124,163],"to":[9,98,120,164],"segmentation":[11,110,166],"remote":[13,168],"sensing":[14,169],"images":[15,170],"multispectral":[17],"SPOT":[18,99],"and":[19,34,100,125,156],"fully":[20],"polarimetric":[21,132],"SAR":[22,101,133],"data.":[23],"The":[24,42,81,154],"structure":[25],"is":[29,35,48,58,83,93,116,171],"modified":[31],"multilayer":[32],"perceptron":[33],"trained":[36],"by":[37],"Kalman":[39,75,151],"filter":[40,152],"theory.":[41],"internal":[43],"activity":[44],"nonlinear":[50],"function,":[51,67],"while":[52,112],"function":[54],"at":[55],"output":[56],"layer":[57],"linearized":[59],"through":[60,146],"use":[62,148],"polynomial":[65],"basis":[66],"thus":[68],"allowing":[69],"us":[70],"employ":[71],"theory":[73],"filtering":[76],"as":[77],"learning":[79,88,114],"rule.":[80],"therefore":[84],"called":[85],"dynamic":[87],"(DL)":[89],"network.":[91],"It":[92],"found":[94],"that,":[95],"when":[96],"applied":[97],"data,":[102,134],"DL":[104,161],"gives":[107],"good":[109],"results,":[111],"rate":[115],"very":[117],"promising":[118],"compared":[119],"standard":[122],"backpropagation":[123],"other":[126],"fast-learning":[127],"networks.":[128],"In":[129],"particular,":[130],"for":[131,137],"optimum":[135],"polarizations":[136],"discriminating":[138],"between":[139],"different":[140],"terrains":[141],"are":[142],"automatically":[143],"built":[144],"in":[145],"technique.":[153],"suitability":[155],"effectiveness":[157],"proposed":[160],"demonstrated.":[172],"\u00a9":[173],"1996":[174],"John":[175],"Wiley":[176],"&":[177],"Sons,":[178],"Inc.":[179]},"counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
