{"id":"https://openalex.org/W3007470918","doi":"https://doi.org/10.1109/tgrs.2020.2971716","title":"Adaptive MultiScale Segmentations for Hyperspectral Image Classification","display_name":"Adaptive MultiScale Segmentations for Hyperspectral Image Classification","publication_year":2020,"publication_date":"2020-02-19","ids":{"openalex":"https://openalex.org/W3007470918","doi":"https://doi.org/10.1109/tgrs.2020.2971716","mag":"3007470918"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2020.2971716","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2020.2971716","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/A5015552513","display_name":"Qingming Leng","orcid":"https://orcid.org/0000-0002-9395-5863"},"institutions":[{"id":"https://openalex.org/I134626604","display_name":"Jiujiang University","ror":"https://ror.org/0066vpg85","country_code":"CN","type":"education","lineage":["https://openalex.org/I134626604"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Qingming Leng","raw_affiliation_strings":["School of Information Science and Technology, Jiujiang University, Jiujiang, China"],"affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, Jiujiang University, Jiujiang, China","institution_ids":["https://openalex.org/I134626604"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031746055","display_name":"Haiou Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I134626604","display_name":"Jiujiang University","ror":"https://ror.org/0066vpg85","country_code":"CN","type":"education","lineage":["https://openalex.org/I134626604"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haiou Yang","raw_affiliation_strings":["College of Tourism and Geography, Jiujiang University, Jiujiang, China"],"affiliations":[{"raw_affiliation_string":"College of Tourism and Geography, Jiujiang University, Jiujiang, China","institution_ids":["https://openalex.org/I134626604"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087165831","display_name":"Junjun Jiang","orcid":"https://orcid.org/0000-0002-5694-505X"},"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":"Junjun Jiang","raw_affiliation_strings":["School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5111504451","display_name":"Qi Tian","orcid":"https://orcid.org/0009-0003-2676-5300"},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qi Tian","raw_affiliation_strings":["Huawei Noah\u2019s Ark Lab, Shenzhen, China","Huawei Noah's Ark Lab, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Huawei Noah\u2019s Ark Lab, Shenzhen, China","institution_ids":["https://openalex.org/I2250955327"]},{"raw_affiliation_string":"Huawei Noah's Ark Lab, Shenzhen, China","institution_ids":["https://openalex.org/I2250955327"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5015552513"],"corresponding_institution_ids":["https://openalex.org/I134626604"],"apc_list":null,"apc_paid":null,"fwci":2.4813,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":{"value":0.91037736,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"58","issue":"8","first_page":"5847","last_page":"5860"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":1.0,"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":1.0,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9908999800682068,"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":0.9868000149726868,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.8331557512283325},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7061275243759155},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6912804245948792},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6907811760902405},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.6704537868499756},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6008355617523193},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5762944221496582},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5376732349395752},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5084661245346069},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.48859769105911255},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.36772650480270386},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.06821838021278381}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8331557512283325},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7061275243759155},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6912804245948792},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6907811760902405},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.6704537868499756},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6008355617523193},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5762944221496582},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5376732349395752},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5084661245346069},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.48859769105911255},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.36772650480270386},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.06821838021278381},{"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/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2020.2971716","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2020.2971716","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":[{"score":0.6100000143051147,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G6163493852","display_name":null,"funder_award_id":"61971165","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7124544518","display_name":null,"funder_award_id":"61562048","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":66,"referenced_works":["https://openalex.org/W1484984511","https://openalex.org/W1548953334","https://openalex.org/W1928626817","https://openalex.org/W1939429412","https://openalex.org/W1964315230","https://openalex.org/W2001298023","https://openalex.org/W2008847349","https://openalex.org/W2049444988","https://openalex.org/W2052160904","https://openalex.org/W2070534370","https://openalex.org/W2074506978","https://openalex.org/W2076414618","https://openalex.org/W2085529604","https://openalex.org/W2087263574","https://openalex.org/W2089468765","https://openalex.org/W2096553553","https://openalex.org/W2101711129","https://openalex.org/W2105386417","https://openalex.org/W2106277226","https://openalex.org/W2119531662","https://openalex.org/W2121766492","https://openalex.org/W2130627644","https://openalex.org/W2131697388","https://openalex.org/W2135431554","https://openalex.org/W2136251662","https://openalex.org/W2145023731","https://openalex.org/W2152057649","https://openalex.org/W2303172903","https://openalex.org/W2500751094","https://openalex.org/W2514340250","https://openalex.org/W2518831014","https://openalex.org/W2548791488","https://openalex.org/W2551397753","https://openalex.org/W2586793539","https://openalex.org/W2594372342","https://openalex.org/W2609880332","https://openalex.org/W2613575128","https://openalex.org/W2740578684","https://openalex.org/W2745791577","https://openalex.org/W2764034829","https://openalex.org/W2767651786","https://openalex.org/W2767805377","https://openalex.org/W2768211636","https://openalex.org/W2768537477","https://openalex.org/W2782522152","https://openalex.org/W2791006446","https://openalex.org/W2792167075","https://openalex.org/W2792332881","https://openalex.org/W2808776742","https://openalex.org/W2826818064","https://openalex.org/W2887785636","https://openalex.org/W2890022946","https://openalex.org/W2894165434","https://openalex.org/W2914633159","https://openalex.org/W2940939359","https://openalex.org/W2942454403","https://openalex.org/W2943270518","https://openalex.org/W2945336884","https://openalex.org/W2964808389","https://openalex.org/W3098551073","https://openalex.org/W3100011500","https://openalex.org/W3100499011","https://openalex.org/W3101640299","https://openalex.org/W3154664134","https://openalex.org/W4250533120","https://openalex.org/W4288076010"],"related_works":["https://openalex.org/W2072166414","https://openalex.org/W3209970181","https://openalex.org/W2070598848","https://openalex.org/W3034375524","https://openalex.org/W2027399350","https://openalex.org/W2060875994","https://openalex.org/W2044184146","https://openalex.org/W2019190440","https://openalex.org/W2067727414","https://openalex.org/W1522196789"],"abstract_inverted_index":{"The":[0,37,196],"number":[1,116],"of":[2,40,83,102,117,172,239],"superpixels":[3,155],"(i.e.,":[4],"segmentation":[5,20,100],"scale)":[6],"is":[7,28,44,61,104,164,189],"crucial":[8],"for":[9,32,54],"spectral-spatial":[10],"hyperspectral":[11,91],"image":[12,108],"(HSI)":[13],"classification.":[14],"Existing":[15],"methods":[16],"always":[17],"set":[18,63,82],"the":[19,51,58,96,99,107,111,115,143,170,173,176,179,192,204,211,216,237,240],"scale":[21,53,59,101,127,131,177,213,219],"through":[22],"a":[23,70,81,125,136,150],"manually":[24],"experimental":[25,228],"strategy,":[26],"which":[27,184],"time-consuming":[29],"and":[30,114,149,166,207],"unsuitable":[31],"various":[33],"complicated":[34],"practical":[35],"applications.":[36],"information":[38],"fusion":[39],"complementary":[41,225],"multiple":[42],"scales":[43,85,199],"proven":[45],"to":[46,89,106,123,168,210],"be":[47],"more":[48],"effective":[49],"than":[50],"single":[52],"HSI":[55,103,232],"classification,":[56],"but":[57],"level":[60],"still":[62],"manually.":[64],"In":[65],"this":[66],"article,":[67],"we":[68],"propose":[69],"novel":[71],"adaptive":[72],"multiscale":[73],"segmentations":[74],"(AMSs)":[75],"method":[76],"that":[77,86,98,133],"can":[78,220],"automatically":[79],"provide":[80,223],"suitable":[84,198],"are":[87,121,200],"adapted":[88],"different":[90],"data.":[92],"Specifically,":[93],"based":[94],"on":[95,230],"assumption":[97],"related":[105],"complexity":[109],"itself,":[110],"texture":[112],"ratio":[113],"land":[118],"cover":[119],"classes":[120],"used":[122],"examine":[124],"candidate":[126],"pool.":[128],"A":[129],"good":[130],"means":[132],"it":[134],"contains":[135],"small":[137],"spectral":[138],"difference":[139],"between":[140,153],"pixels":[141],"within":[142],"same":[144],"superpixel":[145],"(intrasuperpixel":[146],"discrimination":[147,157,162,182],"index)":[148],"large":[151],"discrepancy":[152],"neighboring":[154],"(intersuperpixel":[156],"index).":[158],"Thus,":[159],"an":[160],"intra-interscale":[161],"index":[163],"defined":[165],"applied":[167],"depict":[169],"characteristics":[171],"scale.":[174,195],"Then,":[175],"with":[178,203,245],"best":[180],"intra-inter":[181],"index,":[183],"usually":[185],"has":[186],"satisfactory":[187],"performance,":[188],"treated":[190],"as":[191],"initially":[193],"selected":[194,205],"remaining":[197],"iteratively":[201],"compared":[202,244],"ones":[206],"then":[208],"added":[209,218],"target":[212],"pool,":[214],"until":[215],"newly":[217],"no":[221],"longer":[222],"significantly":[224],"information.":[226],"Extensive":[227],"results":[229],"three":[231],"data":[233],"sets":[234],"have":[235],"demonstrated":[236],"effectiveness":[238],"proposed":[241],"AMS":[242],"when":[243],"state-of-the-art":[246],"methods.":[247]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
