{"id":"https://openalex.org/W7098835019","doi":null,"title":"Youth Forum","display_name":"Youth Forum","publication_year":2011,"publication_date":"2011-03-22","ids":{"openalex":"https://openalex.org/W7098835019"},"language":"en","primary_location":{"id":"pmh:oai:CiteSeerX.psu:10.1.1.184.4553","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.184.4553","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.isprs.org/proceedings/XXXVII/congress/6b_pdf/53.pdf","raw_type":"text"},"volume":null,"type":"article","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Huan Li A","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huan Li A","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Hongxia Luo A","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hongxia Luo A","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Ziyi Zhu B","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ziyi Zhu B","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Guangpeng Liu A","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guangpeng Liu A","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.59395785,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","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/T10689","display_name":"Remote-Sensing Image Classification","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/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":9.999999747378752e-05,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.0,"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/hyperspectral-image-classification","display_name":"hyperspectral image classification","score":0.8790000081062317},{"id":"https://openalex.org/keywords/uncertainty-estimation","display_name":"uncertainty estimation","score":0.972000002861023},{"id":"https://openalex.org/keywords/fuzzy-clustering","display_name":"fuzzy clustering","score":0.9229999780654907},{"id":"https://openalex.org/keywords/neural-network","display_name":"artificial neural networks","score":0.7260000109672546},{"id":"https://openalex.org/keywords/back-propagation-neural-network","display_name":"BP neural network","score":0.8410000205039978},{"id":"https://openalex.org/keywords/misclassification","display_name":"misclassification","score":0.6499999761581421},{"id":"https://openalex.org/keywords/spectral-dimension","display_name":"spectral dimension","score":0.40400001406669617}],"concepts":[{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.7008000016212463},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.621399998664856},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5723999738693237},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5716000199317932},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.5450999736785889},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5393000245094299},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.4426000118255615},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42480000853538513},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4185999929904938},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.4174000024795532},{"id":"https://openalex.org/C42011625","wikidata":"https://www.wikidata.org/wiki/Q1055058","display_name":"Fuzzy set","level":3,"score":0.36419999599456787},{"id":"https://openalex.org/C137209882","wikidata":"https://www.wikidata.org/wiki/Q1403517","display_name":"Measurement uncertainty","level":2,"score":0.329800009727478},{"id":"https://openalex.org/C29470771","wikidata":"https://www.wikidata.org/wiki/Q4165150","display_name":"Neuro-fuzzy","level":4,"score":0.322299987077713},{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.3061000108718872},{"id":"https://openalex.org/C110083411","wikidata":"https://www.wikidata.org/wiki/Q1744628","display_name":"Statistical classification","level":2,"score":0.2955999970436096},{"id":"https://openalex.org/C2780724565","wikidata":"https://www.wikidata.org/wiki/Q5227256","display_name":"Data classification","level":2,"score":0.2881999909877777},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.28040000796318054},{"id":"https://openalex.org/C127385683","wikidata":"https://www.wikidata.org/wiki/Q1475696","display_name":"Fuzzy classification","level":4,"score":0.27459999918937683},{"id":"https://openalex.org/C17212007","wikidata":"https://www.wikidata.org/wiki/Q5511111","display_name":"Fuzzy clustering","level":3,"score":0.27410000562667847},{"id":"https://openalex.org/C195975749","wikidata":"https://www.wikidata.org/wiki/Q1475705","display_name":"Fuzzy control system","level":3,"score":0.27059999108314514},{"id":"https://openalex.org/C175202392","wikidata":"https://www.wikidata.org/wiki/Q2434543","display_name":"Time delay neural network","level":3,"score":0.26750001311302185},{"id":"https://openalex.org/C2781170535","wikidata":"https://www.wikidata.org/wiki/Q30587856","display_name":"Noisy data","level":2,"score":0.26100000739097595},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.25290000438690186}],"mesh":[],"locations_count":1,"locations":[{"id":"pmh:oai:CiteSeerX.psu:10.1.1.184.4553","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.184.4553","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.isprs.org/proceedings/XXXVII/congress/6b_pdf/53.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2618562260","https://openalex.org/W2354784619","https://openalex.org/W2119511317","https://openalex.org/W2380269727","https://openalex.org/W2367693116","https://openalex.org/W3165457871","https://openalex.org/W2074745696","https://openalex.org/W7160158541","https://openalex.org/W2910306855","https://openalex.org/W2791603829"],"abstract_inverted_index":{"Effective":[0],"and":[1,22,60,82,113,121,185],"understanding":[2],"exploration":[3],"of":[4,12,52,118,149],"hyperspectral":[5,103],"remote":[6,104],"sensing":[7,105],"data":[8,184],"necessitates":[9],"the":[10,33,50,83,141,146,150,161,173,182,187],"development":[11],"sophisticated":[13],"schemes":[14,19],"that":[15,91],"represent":[16],"images.":[17],"Such":[18],"ideally":[20],"preserve":[21],"recognize":[23],"significant":[24],"features.":[25],"However,":[26],"uncertainty":[27,53,71,97],"arises":[28],"in":[29,102],"classification":[30,54,110,142,156],"problems":[31],"when":[32],"input":[34,126,151],"pattern":[35,152],"is":[36,42,107,139],"not":[37],"perfect":[38],"or":[39],"measurement":[40,148],"error":[41],"unavoidable.":[43],"It":[44],"would":[45],"be":[46],"need":[47],"to":[48],"obtain":[49],"estimation":[51,98],"associated":[55,153],"with":[56,154,164,189],"a":[57,64],"new":[58],"observation":[59],"its":[61],"membership":[62,85],"within":[63],"particular":[65],"class.":[66,157],"Typically,":[67],"existing":[68],"methods":[69,178],"supplying":[70],"information":[72],"has":[73],"monotonic":[74],"neural":[75,122,133,162],"network":[76,123,163],"model,":[77],"back":[78],"propagation":[79],"NN":[80,170],"(BPNN)":[81],"fuzzy":[84,119,137],"model":[86],"(FMM).":[87],"The":[88,116],"paper":[89],"describes":[90],"an":[92],"efficient":[93],"combinational":[94],"algorithm":[95],"for":[96,109,179],"on":[99,136,145],"spectral":[100],"dimension":[101],"images":[106],"proposed":[108,160],"accuracy":[111],"improvement":[112],"computing":[114],"efficiency.":[115],"combination":[117],"clustering":[120],"adopted,":[124],"which":[125],"patterns":[127],"are":[128],"divided":[129],"into":[130],"several":[131],"small":[132],"networks":[134],"based":[135,144],"clustering,":[138],"provides":[140],"boundaries":[143],"degree-of-dissimilarity":[147],"each":[155],"And":[158],"we":[159],"dynamical":[165],"neuron":[166],"created":[167],"during":[168],"learning":[169],"algorithm.":[171],"In":[172],"experiment,":[174],"We":[175],"tested":[176],"three":[177],"misclassification":[180],"using":[181],"same":[183],"compared":[186],"performances":[188],"our":[190],"method.":[191],"1.":[192]},"counts_by_year":[],"updated_date":"2026-08-26T07:47:46.906454","created_date":"2025-10-27T00:00:00"}
