{"id":"https://openalex.org/W2890306271","doi":"https://doi.org/10.1109/icip.2018.8451145","title":"Iterative Support Vector Machine for Hyperspectral Image Classification","display_name":"Iterative Support Vector Machine for Hyperspectral Image Classification","publication_year":2018,"publication_date":"2018-09-07","ids":{"openalex":"https://openalex.org/W2890306271","doi":"https://doi.org/10.1109/icip.2018.8451145","mag":"2890306271"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2018.8451145","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2018.8451145","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 25th IEEE International Conference on Image Processing (ICIP)","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/A5028696487","display_name":"Shengwei Zhong","orcid":"https://orcid.org/0000-0001-8317-728X"},"institutions":[{"id":"https://openalex.org/I79272384","display_name":"University of Maryland, Baltimore County","ror":"https://ror.org/02qskvh78","country_code":"US","type":"education","lineage":["https://openalex.org/I79272384"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Shengwei Zhong","raw_affiliation_strings":["Department of Computer Science and Electrical Engineering, University of-Maryland, Baltimore County, Baltimore, MD, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Electrical Engineering, University of-Maryland, Baltimore County, Baltimore, MD, USA","institution_ids":["https://openalex.org/I79272384"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Chein-I Chang","orcid":null},"institutions":[{"id":"https://openalex.org/I79272384","display_name":"University of Maryland, Baltimore County","ror":"https://ror.org/02qskvh78","country_code":"US","type":"education","lineage":["https://openalex.org/I79272384"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chein-I Chang","raw_affiliation_strings":["Department of Computer Science and Electrical Engineering, University of-Maryland, Baltimore County, Baltimore, MD, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Electrical Engineering, University of-Maryland, Baltimore County, Baltimore, MD, USA","institution_ids":["https://openalex.org/I79272384"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100449291","display_name":"Ye Zhang","orcid":"https://orcid.org/0000-0001-8721-4535"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ye Zhang","raw_affiliation_strings":["Department of Information Engineering, Harbin Institute of Technology, Harbin, China"],"affiliations":[{"raw_affiliation_string":"Department of Information Engineering, Harbin Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I204983213"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5028696487"],"corresponding_institution_ids":["https://openalex.org/I79272384"],"apc_list":null,"apc_paid":null,"fwci":3.5551,"has_fulltext":false,"cited_by_count":47,"citation_normalized_percentile":{"value":0.93629739,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"3309","last_page":"3312"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9998999834060669,"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":0.9998999834060669,"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/T13890","display_name":"Remote Sensing and Land Use","score":0.9965000152587891,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.9365000128746033,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"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/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.889434814453125},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.778289794921875},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6635816693305969},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6475006937980652},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6361966133117676},{"id":"https://openalex.org/keywords/cube","display_name":"Cube (algebra)","score":0.5446644425392151},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.4853726625442505},{"id":"https://openalex.org/keywords/data-cube","display_name":"Data cube","score":0.4845280051231384},{"id":"https://openalex.org/keywords/iterative-and-incremental-development","display_name":"Iterative and incremental development","score":0.46869754791259766},{"id":"https://openalex.org/keywords/iterative-method","display_name":"Iterative method","score":0.4589764475822449},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.4482637643814087},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3248676061630249},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.30807560682296753},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1997680366039276},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.16873368620872498}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.889434814453125},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.778289794921875},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6635816693305969},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6475006937980652},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6361966133117676},{"id":"https://openalex.org/C53051483","wikidata":"https://www.wikidata.org/wiki/Q861555","display_name":"Cube (algebra)","level":2,"score":0.5446644425392151},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.4853726625442505},{"id":"https://openalex.org/C78168278","wikidata":"https://www.wikidata.org/wiki/Q5227269","display_name":"Data cube","level":2,"score":0.4845280051231384},{"id":"https://openalex.org/C143587482","wikidata":"https://www.wikidata.org/wiki/Q1543216","display_name":"Iterative and incremental development","level":2,"score":0.46869754791259766},{"id":"https://openalex.org/C159694833","wikidata":"https://www.wikidata.org/wiki/Q2321565","display_name":"Iterative method","level":2,"score":0.4589764475822449},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.4482637643814087},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3248676061630249},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.30807560682296753},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1997680366039276},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.16873368620872498},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2018.8451145","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2018.8451145","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 25th IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W1997565609","https://openalex.org/W2012558304","https://openalex.org/W2087263574","https://openalex.org/W2105386417","https://openalex.org/W2114819256","https://openalex.org/W2136251662","https://openalex.org/W2144966944","https://openalex.org/W2151351889","https://openalex.org/W2166923144","https://openalex.org/W2500751094"],"related_works":["https://openalex.org/W1982418987","https://openalex.org/W2087724950","https://openalex.org/W3112209948","https://openalex.org/W2889956472","https://openalex.org/W2366586806","https://openalex.org/W2407777725","https://openalex.org/W4386427838","https://openalex.org/W3178760882","https://openalex.org/W1969639826","https://openalex.org/W1582972698"],"abstract_inverted_index":{"In":[0,46,81],"hyperspectral":[1,35,51,114,151],"image":[2,36,60,142],"classification":[3,15,37,79,152,165],"spectral":[4],"information":[5,8,41,94],"and":[6,61],"spatial":[7,40,93],"are":[9,144],"always":[10],"integrated":[11],"to":[12,27,33,70,75,90,108],"improve":[13],"the":[14,58,71,92,96,101,111,117,125,137],"accuracy.":[16,166],"This":[17],"paper":[18],"develops":[19],"an":[20,49,77,128],"iterative":[21,30,126],"version":[22],"of":[23,95,120,139],"support":[24],"vector":[25],"machine,":[26],"be":[28],"called":[29],"SVM":[31,66],"(ISVM)":[32],"perform":[34],"by":[38,56,162],"extracting":[39],"iteratively":[42],"via":[43],"feedback":[44,83],"loops.":[45],"processing":[47],"ISVM":[48,140,159],"initial":[50,78],"data":[52,73],"cube":[53,74,115],"is":[54,67,88,104,132],"obtained":[55],"combining":[57],"original":[59],"its":[62],"first":[63],"principal":[64],"component.":[65],"then":[68],"implemented":[69],"resulting":[72],"produce":[76],"map.":[80],"each":[82],"loop,":[84],"a":[85],"Gaussian":[86],"filter":[87],"applied":[89],"obtain":[91],"SVM-classification":[97],"map":[98,103],"so":[99],"that":[100,158],"Gaussian-filtered":[102],"further":[105],"fed":[106],"back":[107],"combine":[109],"with":[110,148],"currently":[112],"processed":[113],"for":[116,123],"next":[118],"round":[119],"iteration.":[121],"As":[122],"terminating":[124],"process":[127],"automatic":[129],"stopping":[130],"rule":[131],"also":[133],"developed.":[134],"To":[135],"evaluate":[136],"performance":[138],"real":[141],"experiments":[143],"conducted":[145],"in":[146],"comparison":[147],"state-of-the-art":[149],"spectral-spatial":[150],"methods.":[153],"The":[154],"experiment":[155],"results":[156],"demonstrate":[157],"performed":[160],"better":[161],"providing":[163],"higher":[164]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":9},{"year":2020,"cited_by_count":8},{"year":2013,"cited_by_count":1}],"updated_date":"2026-04-16T08:26:57.006410","created_date":"2025-10-10T00:00:00"}