{"id":"https://openalex.org/W4403718757","doi":"https://doi.org/10.48550/arxiv.2409.11619","title":"Hyperspectral Image Classification Based on Faster Residual Multi-branch Spiking Neural Network","display_name":"Hyperspectral Image Classification Based on Faster Residual Multi-branch Spiking Neural Network","publication_year":2024,"publication_date":"2024-09-18","ids":{"openalex":"https://openalex.org/W4403718757","doi":"https://doi.org/10.48550/arxiv.2409.11619"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2409.11619","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2409.11619","pdf_url":"https://arxiv.org/pdf/2409.11619","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2409.11619","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100584309","display_name":"Yang Liu","orcid":"https://orcid.org/0009-0005-4491-9902"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Yang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100445684","display_name":"Yahui Li","orcid":"https://orcid.org/0000-0002-3779-4911"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Yahui","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000860680","display_name":"Rui Li","orcid":"https://orcid.org/0000-0001-8663-2575"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Rui","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024788799","display_name":"Liming Zhou","orcid":"https://orcid.org/0000-0002-7700-8794"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhou, Liming","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063881243","display_name":"Lanxue Dang","orcid":"https://orcid.org/0000-0003-1053-6741"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dang, Lanxue","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008838678","display_name":"Huiyu Mu","orcid":"https://orcid.org/0000-0002-9003-2617"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mu, Huiyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5071670987","display_name":"Qiang Ge","orcid":"https://orcid.org/0000-0003-3516-7022"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ge, Qiang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13890","display_name":"Remote Sensing and Land Use","score":0.8238000273704529,"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"}},"topics":[{"id":"https://openalex.org/T13890","display_name":"Remote Sensing and Land Use","score":0.8238000273704529,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.821399986743927,"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/T12389","display_name":"Infrared Target Detection Methodologies","score":0.7896000146865845,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/residual","display_name":"Residual","score":0.8200681805610657},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.783968448638916},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6247673630714417},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5645570755004883},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5594393014907837},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5531571507453918},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5096368789672852},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.36713799834251404},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.14781677722930908}],"concepts":[{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.8200681805610657},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.783968448638916},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6247673630714417},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5645570755004883},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5594393014907837},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5531571507453918},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5096368789672852},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.36713799834251404},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.14781677722930908}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2409.11619","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2409.11619","pdf_url":"https://arxiv.org/pdf/2409.11619","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"doi:10.48550/arxiv.2409.11619","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2409.11619","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2409.11619","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2409.11619","pdf_url":"https://arxiv.org/pdf/2409.11619","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G989980530","display_name":null,"funder_award_id":"62176087","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":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4403718757.pdf","grobid_xml":"https://content.openalex.org/works/W4403718757.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2072166414","https://openalex.org/W3209970181","https://openalex.org/W2060875994","https://openalex.org/W3034375524","https://openalex.org/W4230131218","https://openalex.org/W2070598848","https://openalex.org/W2404757046","https://openalex.org/W2044184146","https://openalex.org/W4313014865","https://openalex.org/W2019190440"],"abstract_inverted_index":{"Convolutional":[0],"neural":[1,35,78,164,181],"network":[2,19,79,94],"(CNN)":[3],"performs":[4],"well":[5],"in":[6,41,259],"Hyperspectral":[7],"Image":[8],"(HSI)":[9],"classification":[10,43,91,176,243,257],"tasks,":[11],"but":[12],"its":[13],"high":[14],"energy":[15,49],"consumption":[16,50],"and":[17,51,137,199,220,227,265],"complex":[18],"structure":[20],"make":[21],"it":[22,27,56],"difficult":[23],"to":[24,28,46,63,69,107],"directly":[25,160],"apply":[26],"edge":[29,260],"computing":[30],"devices.":[31,267],"At":[32],"present,":[33],"spiking":[34,77,97,113,121,180],"networks":[36,182],"(SNN)":[37],"have":[38],"developed":[39],"rapidly":[40],"HSI":[42,90,175,242,256],"tasks":[44],"due":[45],"their":[47],"low":[48],"event":[52],"driven":[53],"characteristics.":[54],"However,":[55],"usually":[57],"requires":[58,210],"a":[59,76,135,200,211],"longer":[60],"time":[61,212,222],"step":[62,213],"achieve":[64],"optimal":[65],"accuracy.":[66,232],"In":[67],"response":[68],"the":[70,83,96,104,145,153,193,230,236,252],"above":[71],"problems,":[72],"this":[73,132,167],"paper":[74,133,168],"builds":[75],"(SNN-SWMR)":[80],"based":[81,178,241],"on":[82,179,183],"leaky":[84],"integrate-and-fire":[85],"(LIF)":[86],"neuron":[87],"model":[88],"for":[89,250],"tasks.":[92],"The":[93,112],"uses":[95],"width":[98,114],"mixed":[99,115,122],"residual":[100,116],"(SWMR)":[101],"module":[102,117],"as":[103,263],"basic":[105],"unit":[106],"perform":[108],"feature":[109],"extraction":[110],"operations.":[111],"is":[118],"composed":[119],"of":[120,148,215,224,239,255],"convolution":[123],"(SMC),":[124],"which":[125,143,245],"can":[126,159],"effectively":[127],"extract":[128],"spatial-spectral":[129],"features.":[130],"Secondly,":[131],"designs":[134],"simple":[136],"efficient":[138],"arcsine":[139],"approximate":[140],"derivative":[141],"(AAD),":[142],"solves":[144,235],"non-differentiable":[146],"problem":[147,238],"spike":[149,163],"firing":[150],"by":[151],"fitting":[152,202],"Dirac":[154],"function.":[155],"Through":[156],"AAD,":[157],"we":[158],"train":[161],"supervised":[162],"networks.":[165],"Finally,":[166],"conducts":[169],"comparative":[170],"experiments":[171],"with":[172,206],"multiple":[173],"advanced":[174],"algorithms":[177,258],"six":[184],"public":[185],"hyperspectral":[186],"data":[187],"sets.":[188],"Experimental":[189],"results":[190],"show":[191],"that":[192],"AAD":[194],"function":[195],"has":[196,246],"strong":[197],"robustness":[198],"good":[201],"effect.":[203],"Meanwhile,":[204],"compared":[205],"other":[207],"algorithms,":[208,244],"SNN-SWMR":[209],"reduction":[214,223],"about":[216,225],"84%,":[217],"training":[218],"time,":[219],"testing":[221],"63%":[226],"70%":[228],"at":[229],"same":[231],"This":[233],"study":[234],"key":[237],"SNN":[240],"important":[247],"practical":[248,253],"significance":[249],"promoting":[251],"application":[254],"devices":[261],"such":[262],"spaceborne":[264],"airborne":[266]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2024-10-25T00:00:00"}