{"id":"https://openalex.org/W2519307493","doi":"https://doi.org/10.1109/tgrs.2016.2604290","title":"Random-Walker-Based Collaborative Learning for Hyperspectral Image Classification","display_name":"Random-Walker-Based Collaborative Learning for Hyperspectral Image Classification","publication_year":2016,"publication_date":"2016-09-16","ids":{"openalex":"https://openalex.org/W2519307493","doi":"https://doi.org/10.1109/tgrs.2016.2604290","mag":"2519307493"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2016.2604290","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2016.2604290","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Geoscience and Remote Sensing","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/A5100641761","display_name":"Bin Sun","orcid":"https://orcid.org/0000-0002-7029-8784"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Sun","raw_affiliation_strings":["College of Electrical and Information Engineering, Hunan University, Changsha, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Electrical and Information Engineering, Hunan University, Changsha, China","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057514965","display_name":"Xudong Kang","orcid":"https://orcid.org/0000-0002-3807-2531"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xudong Kang","raw_affiliation_strings":["College of Electrical and Information Engineering, Hunan University, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0002-3807-2531","affiliations":[{"raw_affiliation_string":"College of Electrical and Information Engineering, Hunan University, Changsha, China","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067097659","display_name":"Shutao Li","orcid":"https://orcid.org/0000-0002-0585-9848"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shutao Li","raw_affiliation_strings":["College of Electrical and Information Engineering, Hunan University, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0002-0585-9848","affiliations":[{"raw_affiliation_string":"College of Electrical and Information Engineering, Hunan University, Changsha, China","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035508615","display_name":"J\u00f3n Atli Benediktsson","orcid":"https://orcid.org/0000-0003-0621-9647"},"institutions":[{"id":"https://openalex.org/I165368041","display_name":"University of Iceland","ror":"https://ror.org/01db6h964","country_code":"IS","type":"education","lineage":["https://openalex.org/I165368041"]}],"countries":["IS"],"is_corresponding":false,"raw_author_name":"Jon Atli Benediktsson","raw_affiliation_strings":["Faculty of Electrical and Computer Engineering, University of Iceland, Reykjavik, Iceland"],"raw_orcid":"https://orcid.org/0000-0003-0621-9647","affiliations":[{"raw_affiliation_string":"Faculty of Electrical and Computer Engineering, University of Iceland, Reykjavik, Iceland","institution_ids":["https://openalex.org/I165368041"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":12.1647,"has_fulltext":false,"cited_by_count":66,"citation_normalized_percentile":{"value":0.98797053,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"55","issue":"1","first_page":"212","last_page":"222"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9998000264167786,"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":0.9998000264167786,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9853000044822693,"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/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.9812999963760376,"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":0.8884989023208618},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7336772084236145},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.699918806552887},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6968231201171875},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.617307186126709},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.5430362820625305},{"id":"https://openalex.org/keywords/correctness","display_name":"Correctness","score":0.5240247845649719},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.5006141662597656},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.4265854060649872},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4155727028846741},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.41450533270835876},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3844110369682312},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.11778309941291809}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8884989023208618},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7336772084236145},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.699918806552887},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6968231201171875},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.617307186126709},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.5430362820625305},{"id":"https://openalex.org/C55439883","wikidata":"https://www.wikidata.org/wiki/Q360812","display_name":"Correctness","level":2,"score":0.5240247845649719},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.5006141662597656},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.4265854060649872},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4155727028846741},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.41450533270835876},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3844110369682312},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.11778309941291809}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2016.2604290","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2016.2604290","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Geoscience and Remote Sensing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G8694044906","display_name":null,"funder_award_id":"61601179","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W1964335437","https://openalex.org/W1970945970","https://openalex.org/W1973261010","https://openalex.org/W1985973695","https://openalex.org/W1995653526","https://openalex.org/W2001298023","https://openalex.org/W2016860790","https://openalex.org/W2018482939","https://openalex.org/W2030476695","https://openalex.org/W2043116665","https://openalex.org/W2045095960","https://openalex.org/W2046373373","https://openalex.org/W2059089906","https://openalex.org/W2062432961","https://openalex.org/W2062822804","https://openalex.org/W2064604707","https://openalex.org/W2092869901","https://openalex.org/W2097238823","https://openalex.org/W2101365302","https://openalex.org/W2101711129","https://openalex.org/W2104437233","https://openalex.org/W2105386417","https://openalex.org/W2106777458","https://openalex.org/W2107030918","https://openalex.org/W2114819256","https://openalex.org/W2119363183","https://openalex.org/W2125637308","https://openalex.org/W2131864940","https://openalex.org/W2134663338","https://openalex.org/W2136251662","https://openalex.org/W2144438956","https://openalex.org/W2148791530","https://openalex.org/W2149471024","https://openalex.org/W2150045166","https://openalex.org/W2153409933","https://openalex.org/W2157853947","https://openalex.org/W2158400785","https://openalex.org/W2164437025","https://openalex.org/W2166923144","https://openalex.org/W2313771561"],"related_works":["https://openalex.org/W2072166414","https://openalex.org/W3209970181","https://openalex.org/W2060875994","https://openalex.org/W2786391746","https://openalex.org/W3132346564","https://openalex.org/W4381430104","https://openalex.org/W4226059458","https://openalex.org/W2914559142","https://openalex.org/W2995102745","https://openalex.org/W1990237101"],"abstract_inverted_index":{"Active":[0],"learning":[1,5],"(AL)":[2],"and":[3,25,37,40,62,71,87,105,150],"semisupervised":[4],"(SSL)":[6],"are":[7,79,128],"both":[8],"promising":[9],"solutions":[10],"to":[11,32,49,119,162],"hyperspectral":[12,153,173],"image":[13,154],"classification.":[14],"Given":[15],"a":[16,28,57,141,188],"few":[17,142],"initial":[18,46],"labeled":[19,36,47,138,194],"samples,":[20],"this":[21,123],"work":[22],"combines":[23],"AL":[24,116],"SSL":[26],"in":[27,139],"novel":[29],"manner,":[30],"aiming":[31],"obtain":[33,163],"more":[34,129],"manually":[35,193],"pseudolabeled":[38,109],"samples":[39,48,78,126],"use":[41],"them":[42],"together":[43],"with":[44,145,187],"the":[45,51,60,76,93,103,108,112,125,146,151,157,164,178],"improve":[50],"classification":[52,64,134,166,184],"performance.":[53],"First,":[54],"based":[55],"on":[56,170],"comparison":[58],"of":[59,107,133,192],"segmentation":[61],"spectral-spatial":[63],"results":[65],"obtained":[66],"by":[67],"random":[68],"walker":[69],"(RW)":[70],"extended":[72],"RW":[73],"(ERW)":[74],"algorithms,":[75],"unlabeled":[77,89,95,114],"separated":[80],"into":[81],"two":[82],"different":[83],"sets,":[84],"i.e.,":[85],"low-":[86],"high-confidence":[88,94],"data":[90,174],"sets.":[91],"For":[92,111],"data,":[96,115],"pseudolabeling":[97],"is":[98,117,160],"performed,":[99],"which":[100,127],"can":[101,136,181],"ensure":[102],"correctness":[104],"informativeness":[106],"samples.":[110,121,195],"low-confidence":[113],"used":[118,161],"select":[120],"In":[122],"way,":[124],"effective":[130],"for":[131],"improvement":[132],"performance":[135],"be":[137],"only":[140],"iterations.":[143],"Finally,":[144],"learned":[147],"training":[148],"set":[149],"original":[152],"as":[155],"inputs,":[156],"ERW":[158],"classifier":[159],"final":[165],"result.":[167],"Experiments":[168],"performed":[169],"three":[171],"real":[172],"sets":[175],"show":[176],"that":[177],"proposed":[179],"method":[180],"achieve":[182],"competitive":[183],"accuracy":[185],"even":[186],"very":[189],"limited":[190],"number":[191]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":9},{"year":2019,"cited_by_count":8},{"year":2018,"cited_by_count":16},{"year":2017,"cited_by_count":14}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
