{"id":"https://openalex.org/W3006984222","doi":"https://doi.org/10.1109/tgrs.2020.2967821","title":"FPGA: Fast Patch-Free Global Learning Framework for Fully End-to-End Hyperspectral Image Classification","display_name":"FPGA: Fast Patch-Free Global Learning Framework for Fully End-to-End Hyperspectral Image Classification","publication_year":2020,"publication_date":"2020-02-25","ids":{"openalex":"https://openalex.org/W3006984222","doi":"https://doi.org/10.1109/tgrs.2020.2967821","mag":"3006984222"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2020.2967821","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2020.2967821","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":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2011.05670","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Zhuo Zheng","orcid":"https://orcid.org/0000-0003-1811-6725"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]},{"id":"https://openalex.org/I4210118728","display_name":"State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing","ror":"https://ror.org/02bpap860","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210118728"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhuo Zheng","raw_affiliation_strings":["Hubei Provincial Engineering Research Center of Natural Resources Remote Sensing Monitoring, Wuhan University, Wuhan, China","State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Hubei Provincial Engineering Research Center of Natural Resources Remote Sensing Monitoring, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I4210118728","https://openalex.org/I37461747"]},{"raw_affiliation_string":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I4210118728","https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yanfei Zhong","orcid":"https://orcid.org/0000-0001-9446-5850"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]},{"id":"https://openalex.org/I4210118728","display_name":"State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing","ror":"https://ror.org/02bpap860","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210118728"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanfei Zhong","raw_affiliation_strings":["Hubei Provincial Engineering Research Center of Natural Resources Remote Sensing Monitoring, Wuhan University, Wuhan, China","State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Hubei Provincial Engineering Research Center of Natural Resources Remote Sensing Monitoring, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I4210118728","https://openalex.org/I37461747"]},{"raw_affiliation_string":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I4210118728","https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Ailong Ma","orcid":"https://orcid.org/0000-0003-3692-6473"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]},{"id":"https://openalex.org/I4210118728","display_name":"State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing","ror":"https://ror.org/02bpap860","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210118728"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ailong Ma","raw_affiliation_strings":["Hubei Provincial Engineering Research Center of Natural Resources Remote Sensing Monitoring, Wuhan University, Wuhan, China","State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Hubei Provincial Engineering Research Center of Natural Resources Remote Sensing Monitoring, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I4210118728","https://openalex.org/I37461747"]},{"raw_affiliation_string":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I4210118728","https://openalex.org/I37461747"]}]},{"author_position":"last","author":{"id":null,"display_name":"Liangpei Zhang","orcid":"https://orcid.org/0000-0001-6890-3650"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]},{"id":"https://openalex.org/I4210118728","display_name":"State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing","ror":"https://ror.org/02bpap860","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210118728"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liangpei Zhang","raw_affiliation_strings":["Hubei Provincial Engineering Research Center of Natural Resources Remote Sensing Monitoring, Wuhan University, Wuhan, China","State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Hubei Provincial Engineering Research Center of Natural Resources Remote Sensing Monitoring, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I4210118728","https://openalex.org/I37461747"]},{"raw_affiliation_string":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I4210118728","https://openalex.org/I37461747"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I37461747","https://openalex.org/I4210118728"],"apc_list":null,"apc_paid":null,"fwci":22.5601,"has_fulltext":false,"cited_by_count":207,"citation_normalized_percentile":{"value":0.99540564,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"58","issue":"8","first_page":"5612","last_page":"5626"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9909999966621399,"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":0.9909999966621399,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.0006000000284984708,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.0006000000284984708,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5315999984741211},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.5133000016212463},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5077000260353088},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.4894999861717224},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.43939998745918274},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4318999946117401},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.4117000102996826},{"id":"https://openalex.org/keywords/spatial-analysis","display_name":"Spatial analysis","score":0.39169999957084656},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.375}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7303000092506409},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.651199996471405},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5315999984741211},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.5133000016212463},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5077000260353088},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.4894999861717224},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.43939998745918274},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4318999946117401},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.4117000102996826},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.39169999957084656},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.375},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.3682999908924103},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.362199991941452},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.35280001163482666},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3305000066757202},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.3249000012874603},{"id":"https://openalex.org/C207390915","wikidata":"https://www.wikidata.org/wiki/Q1230525","display_name":"Divergence (linguistics)","level":2,"score":0.32409998774528503},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.2971999943256378},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.28600001335144043},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2854999899864197},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.2815999984741211},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.26809999346733093},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.26499998569488525},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.259799987077713},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.2574000060558319},{"id":"https://openalex.org/C206688291","wikidata":"https://www.wikidata.org/wiki/Q7617819","display_name":"Stochastic gradient descent","level":3,"score":0.25119999051094055}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tgrs.2020.2967821","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2020.2967821","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"},{"id":"pmh:oai:arXiv.org:2011.05670","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2011.05670","pdf_url":"https://arxiv.org/pdf/2011.05670","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2011.05670","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2011.05670","pdf_url":"https://arxiv.org/pdf/2011.05670","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":51,"referenced_works":["https://openalex.org/W1521436688","https://openalex.org/W1903029394","https://openalex.org/W1950365613","https://openalex.org/W1969245801","https://openalex.org/W1971637299","https://openalex.org/W1990653740","https://openalex.org/W1994616650","https://openalex.org/W1998030734","https://openalex.org/W2008847349","https://openalex.org/W2016860790","https://openalex.org/W2029316659","https://openalex.org/W2090424610","https://openalex.org/W2114819256","https://openalex.org/W2130627644","https://openalex.org/W2131438174","https://openalex.org/W2136251662","https://openalex.org/W2150579376","https://openalex.org/W2151665594","https://openalex.org/W2152477088","https://openalex.org/W2164437025","https://openalex.org/W2194775991","https://openalex.org/W2314785379","https://openalex.org/W2412782625","https://openalex.org/W2500751094","https://openalex.org/W2519653196","https://openalex.org/W2524214095","https://openalex.org/W2548791488","https://openalex.org/W2609880332","https://openalex.org/W2732412926","https://openalex.org/W2752782242","https://openalex.org/W2767651786","https://openalex.org/W2768537477","https://openalex.org/W2772452219","https://openalex.org/W2784118841","https://openalex.org/W2791006446","https://openalex.org/W2792332881","https://openalex.org/W2800371750","https://openalex.org/W2804902458","https://openalex.org/W2894165434","https://openalex.org/W2904698365","https://openalex.org/W2907100627","https://openalex.org/W2912961521","https://openalex.org/W2919115771","https://openalex.org/W2942454403","https://openalex.org/W2963366243","https://openalex.org/W2963881378","https://openalex.org/W4250482878","https://openalex.org/W4320339642","https://openalex.org/W6626606588","https://openalex.org/W6639824700","https://openalex.org/W6659717275"],"related_works":["https://openalex.org/W1997670935","https://openalex.org/W2987315422","https://openalex.org/W2005185696","https://openalex.org/W2161229648","https://openalex.org/W2235753890","https://openalex.org/W2366116130","https://openalex.org/W2130228941","https://openalex.org/W1966218515","https://openalex.org/W1533292911","https://openalex.org/W2132132164"],"abstract_inverted_index":{"Deep":[0],"learning":[1,21,36,51],"techniques":[2],"have":[3,39],"provided":[4],"significant":[5],"improvements":[6],"in":[7,108,200,262,269,293],"hyperspectral":[8],"image":[9,26],"(HSI)":[10],"classification.":[11,58,300],"The":[12,59,272],"current":[13],"deep":[14],"learning-based":[15],"HSI":[16,57,122,219,299],"classifiers":[17],"follow":[18],"a":[19,40,47,68,160,181,205,214,237,242],"patch-based":[20,291],"framework":[22,53,61,286,292],"by":[23,101,137,174],"dividing":[24],"the":[25,84,97,103,118,132,138,144,149,177,195,198,201,225,228,234,254,259,263,266,270,284,290],"into":[27,180],"overlapping":[28],"patches.":[29],"As":[30],"such,":[31],"these":[32],"methods":[33],"are":[34],"local":[35],"methods,":[37],"which":[38,106,212],"high":[41],"computational":[42],"cost.":[43],"In":[44,88],"this":[45],"article,":[46],"fast":[48,109,153],"patch-free":[49],"global":[50,98,156,161,229],"(FPGA)":[52],"is":[54,93,113,171,213,221,249,287],"proposed":[55,60,173,222],"for":[56,121,218,298],"consists":[62],"of":[63,152,184,197,208,227],"three":[64,277],"main":[65],"parts:":[66],"1)":[67],"designed":[69,251],"sampling":[70,169],"strategy;":[71],"2)":[72],"an":[73,90],"encoder-decoder-based":[74,91,119],"fully":[75,215],"convolutional":[76],"network":[77,217],"(FCN);":[78],"and":[79,86,147,155,232,241,256,265,296],"3)":[80],"lateral":[81,246],"connections":[82],"between":[83],"encoder":[85,240,255,264],"decoder.":[87,244,271],"FPGA,":[89],"FCN":[92,120,199,209],"utilized":[94],"to":[95,115,128,131,193,223,252,289],"consider":[96],"spatial":[99,157,230,260],"information":[100,158,231],"processing":[102],"whole":[104],"image,":[105],"results":[107,274],"inference.":[110],"However,":[111],"it":[112,125],"difficult":[114],"directly":[116],"utilize":[117],"classification":[123],"as":[124],"always":[126],"fails":[127],"converge":[129],"due":[130],"insufficiently":[133],"diverse":[134,191],"gradients":[135,192],"caused":[136],"limited":[139],"training":[140,178],"samples.":[141,186],"To":[142],"solve":[143],"divergence":[145],"problem":[146],"maintain":[148],"FCNs":[150],"abilities":[151],"inference":[154],"mining,":[159],"stochastic":[162,182],"stratified":[163,185],"(GS":[164],"<sup":[165],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[166],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">2</sup>":[167],")":[168],"strategy":[170,188],"first":[172],"transforming":[175],"all":[176],"samples":[179],"sequence":[183],"This":[187],"can":[189],"obtain":[190],"guarantee":[194],"convergence":[196],"FPGA":[202,285],"framework.":[203],"For":[204],"better":[206],"design":[207],"architecture,":[210],"FreeNet,":[211],"end-to-end":[216],"classification,":[220],"maximize":[224],"exploitation":[226],"boost":[233],"performance":[235],"via":[236],"spectral":[238],"attention-based":[239],"lightweight":[243],"A":[245],"connection":[247],"module":[248],"also":[250],"connect":[253],"decoder,":[257],"fusing":[258],"details":[261],"semantic":[267],"features":[268],"experimental":[273],"obtained":[275],"using":[276],"public":[278],"benchmark":[279],"data":[280],"sets":[281],"suggest":[282],"that":[283],"superior":[288],"both":[294],"speed":[295],"accuracy":[297]},"counts_by_year":[{"year":2026,"cited_by_count":7},{"year":2025,"cited_by_count":30},{"year":2024,"cited_by_count":52},{"year":2023,"cited_by_count":45},{"year":2022,"cited_by_count":47},{"year":2021,"cited_by_count":25},{"year":2020,"cited_by_count":1}],"updated_date":"2026-04-03T22:45:19.894376","created_date":"2020-03-06T00:00:00"}
