{"id":"https://openalex.org/W3120356488","doi":"https://doi.org/10.1109/tgrs.2020.3048128","title":"Attention-Based Second-Order Pooling Network for Hyperspectral Image Classification","display_name":"Attention-Based Second-Order Pooling Network for Hyperspectral Image Classification","publication_year":2021,"publication_date":"2021-01-14","ids":{"openalex":"https://openalex.org/W3120356488","doi":"https://doi.org/10.1109/tgrs.2020.3048128","mag":"3120356488"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2020.3048128","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2020.3048128","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/A5107976561","display_name":"Zhaohui Xue","orcid":"https://orcid.org/0000-0002-1672-317X"},"institutions":[{"id":"https://openalex.org/I163340411","display_name":"Hohai University","ror":"https://ror.org/01wd4xt90","country_code":"CN","type":"education","lineage":["https://openalex.org/I163340411"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhaohui Xue","raw_affiliation_strings":["School of Earth Sciences and Engineering, Hohai University, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-1672-317X","affiliations":[{"raw_affiliation_string":"School of Earth Sciences and Engineering, Hohai University, Nanjing, China","institution_ids":["https://openalex.org/I163340411"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016879046","display_name":"Mengxue Zhang","orcid":"https://orcid.org/0000-0002-8587-4334"},"institutions":[{"id":"https://openalex.org/I163340411","display_name":"Hohai University","ror":"https://ror.org/01wd4xt90","country_code":"CN","type":"education","lineage":["https://openalex.org/I163340411"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mengxue Zhang","raw_affiliation_strings":["School of Earth Sciences and Engineering, Hohai University, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-8587-4334","affiliations":[{"raw_affiliation_string":"School of Earth Sciences and Engineering, Hohai University, Nanjing, China","institution_ids":["https://openalex.org/I163340411"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100782684","display_name":"Yifeng Liu","orcid":"https://orcid.org/0000-0001-7235-5503"},"institutions":[{"id":"https://openalex.org/I4210130112","display_name":"China Academy of Information and Communications Technology","ror":"https://ror.org/038dte259","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210130112","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yifeng Liu","raw_affiliation_strings":["China Academy of Electronics and Information Technology, National Engineering Laboratory for Risk Perception and Prevention (NEL-RPP), Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China Academy of Electronics and Information Technology, National Engineering Laboratory for Risk Perception and Prevention (NEL-RPP), Beijing, China","institution_ids":["https://openalex.org/I4210130112"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100690406","display_name":"Peijun Du","orcid":"https://orcid.org/0000-0002-2488-2656"},"institutions":[{"id":"https://openalex.org/I211433327","display_name":"Ministry of Natural Resources","ror":"https://ror.org/02kxqx159","country_code":"CN","type":"government","lineage":["https://openalex.org/I211433327","https://openalex.org/I4210127390"]},{"id":"https://openalex.org/I4210141657","display_name":"Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application","ror":"https://ror.org/045yewh40","country_code":"CN","type":"facility","lineage":["https://openalex.org/I152031979","https://openalex.org/I4210141657"]},{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peijun Du","raw_affiliation_strings":["Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing University, Nanjing, China","Key Laboratory for Land Satellite Remote Sensing Applications of Ministry of Natural Resources, Nanjing University, Nanjing, China","School of Geography and Ocean Science, Nanjing University, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-2488-2656","affiliations":[{"raw_affiliation_string":"Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I4210141657","https://openalex.org/I881766915"]},{"raw_affiliation_string":"Key Laboratory for Land Satellite Remote Sensing Applications of Ministry of Natural Resources, Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I211433327","https://openalex.org/I881766915"]},{"raw_affiliation_string":"School of Geography and Ocean Science, Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I881766915"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":9.0941,"has_fulltext":false,"cited_by_count":87,"citation_normalized_percentile":{"value":0.9823068,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"59","issue":"11","first_page":"9600","last_page":"9615"},"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":0.9905999898910522,"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":0.9904000163078308,"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/softmax-function","display_name":"Softmax function","score":0.8303134441375732},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.8094592094421387},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.7981878519058228},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7764787673950195},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6914259195327759},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.6664144992828369},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6210699081420898},{"id":"https://openalex.org/keywords/hyperparameter","display_name":"Hyperparameter","score":0.5467341542243958},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4910552501678467},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4868621230125427},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.46999964118003845},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.4685346186161041},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4265219569206238},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.41305720806121826},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3103262782096863},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1457480490207672}],"concepts":[{"id":"https://openalex.org/C188441871","wikidata":"https://www.wikidata.org/wiki/Q7554146","display_name":"Softmax function","level":3,"score":0.8303134441375732},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8094592094421387},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.7981878519058228},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7764787673950195},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6914259195327759},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6664144992828369},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6210699081420898},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.5467341542243958},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4910552501678467},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4868621230125427},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.46999964118003845},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.4685346186161041},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4265219569206238},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.41305720806121826},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3103262782096863},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1457480490207672},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2020.3048128","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2020.3048128","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":0.6800000071525574,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G179363741","display_name":"\u9ad8\u5149\u8c31\u9065\u611f\u5f71\u50cf\u534a\u76d1\u7763\u6df1\u5ea6\u5b66\u4e60\u4e0e\u5206\u7c7b\u7814\u7a76","funder_award_id":"41971279","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8870202964","display_name":null,"funder_award_id":"B200202012","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":63,"referenced_works":["https://openalex.org/W1521436688","https://openalex.org/W1606858007","https://openalex.org/W1950365613","https://openalex.org/W2029316659","https://openalex.org/W2069231830","https://openalex.org/W2090424610","https://openalex.org/W2104657103","https://openalex.org/W2119138423","https://openalex.org/W2119821739","https://openalex.org/W2314785379","https://openalex.org/W2412588858","https://openalex.org/W2500751094","https://openalex.org/W2516282711","https://openalex.org/W2547846938","https://openalex.org/W2548791488","https://openalex.org/W2572303978","https://openalex.org/W2611655888","https://openalex.org/W2614256707","https://openalex.org/W2614326984","https://openalex.org/W2732412926","https://openalex.org/W2743255627","https://openalex.org/W2764034829","https://openalex.org/W2764276316","https://openalex.org/W2767805377","https://openalex.org/W2768975974","https://openalex.org/W2782517596","https://openalex.org/W2782517840","https://openalex.org/W2782522152","https://openalex.org/W2800371750","https://openalex.org/W2800903797","https://openalex.org/W2809113079","https://openalex.org/W2887785636","https://openalex.org/W2894165434","https://openalex.org/W2901461790","https://openalex.org/W2907100627","https://openalex.org/W2908955282","https://openalex.org/W2919115771","https://openalex.org/W2940678725","https://openalex.org/W2942454403","https://openalex.org/W2950266692","https://openalex.org/W2954930822","https://openalex.org/W2962770389","https://openalex.org/W2964054038","https://openalex.org/W2964231884","https://openalex.org/W2966751049","https://openalex.org/W2969508585","https://openalex.org/W2977002487","https://openalex.org/W2989871747","https://openalex.org/W2991286101","https://openalex.org/W2991494819","https://openalex.org/W2991616716","https://openalex.org/W3003369751","https://openalex.org/W3004925702","https://openalex.org/W3006984222","https://openalex.org/W3031015423","https://openalex.org/W3037409780","https://openalex.org/W3098388691","https://openalex.org/W3100011500","https://openalex.org/W3100826601","https://openalex.org/W3101640299","https://openalex.org/W3103753223","https://openalex.org/W4239510810","https://openalex.org/W4240485910"],"related_works":["https://openalex.org/W3095152779","https://openalex.org/W3119773509","https://openalex.org/W3128220219","https://openalex.org/W3134502938","https://openalex.org/W2748667022","https://openalex.org/W4229443568","https://openalex.org/W2761785940","https://openalex.org/W3211770882","https://openalex.org/W2129933262","https://openalex.org/W2010629964"],"abstract_inverted_index":{"Deep":[0],"learning":[1],"(DL)":[2],"has":[3,29],"exhibited":[4],"huge":[5],"potentials":[6],"for":[7,143,173],"hyperspectral":[8,182],"image":[9],"(HSI)":[10],"classification":[11,174,195,206],"due":[12],"to":[13,47,111,127],"its":[14],"powerful":[15],"nonlinear":[16],"modeling":[17],"and":[18,74,80,130,170,191,210],"end-to-end":[19,155],"optimization":[20,66],"characteristics.":[21],"Although":[22],"the":[23,39,62,65,71,86,113],"superior":[24],"performance":[25,201],"of":[26,67,116,162,199],"DL-based":[27,193],"methods":[28,196],"been":[30],"witnessed,":[31],"some":[32],"limitations":[33],"can":[34,148],"still":[35],"be":[36],"found.":[37],"On":[38,61],"one":[40],"hand,":[41,64],"existing":[42],"DL":[43,88],"frameworks":[44],"usually":[45],"resorted":[46],"first-order":[48,106],"statistical":[49,59,151],"features,":[50],"whereas":[51],"they":[52],"rarely":[53],"considered":[54],"second-order":[55,100,121,150],"or":[56],"higher":[57],"order":[58],"features.":[60,132],"other":[63,189],"complex":[68,163],"hyperparameters":[69,164],"(e.g.,":[70],"layer":[72,137],"number":[73],"convolutional":[75],"kernel":[76],"size)":[77],"is":[78,109,125,141,160],"time-consuming":[79],"a":[81,97,105,134],"very":[82],"tough":[83],"task,":[84],"making":[85,166],"designed":[87,110,126],"framework":[89,147],"unexplainable.":[90],"To":[91],"overcome":[92],"these":[93],"challenges,":[94],"we":[95],"propose":[96],"novel":[98],"attention-based":[99,120],"pooling":[101,122],"network":[102],"(A-SPN).":[103],"First,":[104],"feature":[107],"operator":[108,124],"model":[112,128],"spectral\u2013spatial":[114],"information":[115],"HSI.":[117],"Second,":[118],"an":[119,154],"(A-SOP)":[123],"discriminative":[129],"representative":[131],"Finally,":[133],"fully":[135],"connected":[136],"with":[138,202],"softmax":[139],"loss":[140],"used":[142],"classification.":[144],"The":[145],"proposed":[146],"obtain":[149],"features":[152],"in":[153,197],"manner.":[156],"In":[157],"addition,":[158],"A-SPN":[159,187],"free":[161],"tuning,":[165],"it":[167],"more":[168],"explainable":[169],"easily":[171],"equipped":[172],"tasks.":[175],"Experimental":[176],"results":[177],"based":[178],"on":[179],"three":[180],"common":[181],"data":[183],"sets":[184],"demonstrate":[185],"that":[186],"outperforms":[188],"traditional":[190],"state-of-the-art":[192],"HSI":[194],"terms":[198],"generalization":[200],"limited":[203],"training":[204],"samples,":[205],"accuracy,":[207],"convergence":[208],"rate,":[209],"computational":[211],"complexity.":[212]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":17},{"year":2023,"cited_by_count":27},{"year":2022,"cited_by_count":20},{"year":2021,"cited_by_count":9}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}