{"id":"https://openalex.org/W4387802558","doi":"https://doi.org/10.1109/igarss52108.2023.10282167","title":"Hyperspectral Image Classification Via Multi-Scale Residual Attention Network","display_name":"Hyperspectral Image Classification Via Multi-Scale Residual Attention Network","publication_year":2023,"publication_date":"2023-07-16","ids":{"openalex":"https://openalex.org/W4387802558","doi":"https://doi.org/10.1109/igarss52108.2023.10282167"},"language":"en","primary_location":{"id":"doi:10.1109/igarss52108.2023.10282167","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss52108.2023.10282167","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-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/A5066026113","display_name":"Wen Xie","orcid":"https://orcid.org/0000-0002-8111-8195"},"institutions":[{"id":"https://openalex.org/I4210136859","display_name":"Xi\u2019an University of Posts and Telecommunications","ror":"https://ror.org/04jn0td46","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210136859"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wen Xie","raw_affiliation_strings":["Xi&#x2019;an University of Posts and Telecommunications,School of Communications and Information Engineering,Xi&#x2019;an,China,710121"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xi&#x2019;an University of Posts and Telecommunications,School of Communications and Information Engineering,Xi&#x2019;an,China,710121","institution_ids":["https://openalex.org/I4210136859"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078434282","display_name":"Qinzhe Wu","orcid":"https://orcid.org/0000-0002-7988-1431"},"institutions":[{"id":"https://openalex.org/I4210136859","display_name":"Xi\u2019an University of Posts and Telecommunications","ror":"https://ror.org/04jn0td46","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210136859"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qinzhe Wu","raw_affiliation_strings":["Xi&#x2019;an University of Posts and Telecommunications,School of Communications and Information Engineering,Xi&#x2019;an,China,710121"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xi&#x2019;an University of Posts and Telecommunications,School of Communications and Information Engineering,Xi&#x2019;an,China,710121","institution_ids":["https://openalex.org/I4210136859"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033209477","display_name":"Wen Ren","orcid":"https://orcid.org/0000-0001-8373-4867"},"institutions":[{"id":"https://openalex.org/I4210136859","display_name":"Xi\u2019an University of Posts and Telecommunications","ror":"https://ror.org/04jn0td46","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210136859"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wen Ren","raw_affiliation_strings":["Xi&#x2019;an University of Posts and Telecommunications,School of Communications and Information Engineering,Xi&#x2019;an,China,710121"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xi&#x2019;an University of Posts and Telecommunications,School of Communications and Information Engineering,Xi&#x2019;an,China,710121","institution_ids":["https://openalex.org/I4210136859"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102002177","display_name":"Yuzhuo Zhang","orcid":"https://orcid.org/0000-0003-2380-2922"},"institutions":[{"id":"https://openalex.org/I4210136859","display_name":"Xi\u2019an University of Posts and Telecommunications","ror":"https://ror.org/04jn0td46","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210136859"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuzhuo Zhang","raw_affiliation_strings":["Xi&#x2019;an University of Posts and Telecommunications,School of Communications and Information Engineering,Xi&#x2019;an,China,710121"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xi&#x2019;an University of Posts and Telecommunications,School of Communications and Information Engineering,Xi&#x2019;an,China,710121","institution_ids":["https://openalex.org/I4210136859"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1501,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.51308612,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"7649","last_page":"7652"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9868999719619751,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9835000038146973,"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/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.9449617862701416},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.741270899772644},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7177579998970032},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.6879732012748718},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6796174049377441},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6602290868759155},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.6147068738937378},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4691694378852844},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.45890042185783386},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4514169692993164},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.40934208035469055},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.1302068531513214}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.9449617862701416},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.741270899772644},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7177579998970032},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.6879732012748718},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6796174049377441},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6602290868759155},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.6147068738937378},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4691694378852844},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.45890042185783386},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4514169692993164},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.40934208035469055},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.1302068531513214},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss52108.2023.10282167","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss52108.2023.10282167","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"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":12,"referenced_works":["https://openalex.org/W1966580635","https://openalex.org/W2120641342","https://openalex.org/W2793941577","https://openalex.org/W2884585870","https://openalex.org/W2914331134","https://openalex.org/W2963125010","https://openalex.org/W3022592629","https://openalex.org/W3031696400","https://openalex.org/W3094695322","https://openalex.org/W3170347305","https://openalex.org/W4288257146","https://openalex.org/W6781550413"],"related_works":["https://openalex.org/W2072166414","https://openalex.org/W2964954556","https://openalex.org/W2952813363","https://openalex.org/W4360783045","https://openalex.org/W2963346891","https://openalex.org/W3176438653","https://openalex.org/W2770149305","https://openalex.org/W3167930666","https://openalex.org/W3014952856","https://openalex.org/W3010730661"],"abstract_inverted_index":{"The":[0],"application":[1],"of":[2,10,44,56,90,112],"convolutional":[3],"neural":[4],"network":[5,45,48,74,86,115],"(CNN)":[6],"in":[7],"the":[8,38,41,47,54,65,84,88,109,113],"field":[9],"hyperspectral":[11,19,104],"image":[12,105],"(HSI)":[13],"classification":[14,49,110],"has":[15],"been":[16],"pervasive.":[17],"Since":[18],"images":[20],"contain":[21],"numerous":[22],"complicated":[23],"spectral-spatial":[24],"information,":[25],"only":[26],"using":[27],"a":[28,70],"single-channel":[29],"CNN":[30],"is":[31],"difficult":[32],"to":[33,63,75],"fully":[34],"extract":[35,76],"information":[36],"from":[37,78],"images.":[39],"As":[40],"increasing":[42],"number":[43,55,89],"layers,":[46],"accuracy":[50],"will":[51,58],"decrease,":[52],"and":[53],"parameters":[57,91],"increase":[59],"greatly.":[60],"In":[61,82],"order":[62],"avoid":[64],"above":[66],"defects,":[67],"we":[68],"propose":[69],"multi-scale":[71],"residual":[72],"attention":[73],"features":[77],"HSI":[79],"more":[80],"efficiently.":[81],"addition,":[83],"proposed":[85,114],"lowers":[87],"by":[92],"introducing":[93],"depthwise":[94],"separable":[95],"convolution":[96],"(DSC).":[97],"Experimental":[98],"studies":[99],"on":[100],"two":[101],"commonly":[102],"used":[103],"datasets":[106],"verify":[107],"that":[108],"performance":[111],"outperforms":[116],"some":[117],"state-of-the-art":[118],"networks.":[119]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
