{"id":"https://openalex.org/W3207368019","doi":"https://doi.org/10.1109/igarss47720.2021.9555010","title":"A Novel Classification Framework for Hyperspectral Image Classification Based on Multi-Scale Dense Network","display_name":"A Novel Classification Framework for Hyperspectral Image Classification Based on Multi-Scale Dense Network","publication_year":2021,"publication_date":"2021-07-11","ids":{"openalex":"https://openalex.org/W3207368019","doi":"https://doi.org/10.1109/igarss47720.2021.9555010","mag":"3207368019"},"language":"en","primary_location":{"id":"doi:10.1109/igarss47720.2021.9555010","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss47720.2021.9555010","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS","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/A5100396842","display_name":"Hao Zhang","orcid":"https://orcid.org/0000-0002-0206-9381"},"institutions":[{"id":"https://openalex.org/I43313876","display_name":"Dalian Maritime University","ror":"https://ror.org/002b7nr53","country_code":"CN","type":"education","lineage":["https://openalex.org/I43313876"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hao Zhang","raw_affiliation_strings":["Center of Hyperspectral Imaging in Remote Sensing (CHIRS), Information Science and Technology College, Dalian Maritime University, Dalian, China"],"affiliations":[{"raw_affiliation_string":"Center of Hyperspectral Imaging in Remote Sensing (CHIRS), Information Science and Technology College, Dalian Maritime University, Dalian, China","institution_ids":["https://openalex.org/I43313876"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081712622","display_name":"Haoyang Yu","orcid":"https://orcid.org/0000-0002-4026-7450"},"institutions":[{"id":"https://openalex.org/I43313876","display_name":"Dalian Maritime University","ror":"https://ror.org/002b7nr53","country_code":"CN","type":"education","lineage":["https://openalex.org/I43313876"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haoyang Yu","raw_affiliation_strings":["Center of Hyperspectral Imaging in Remote Sensing (CHIRS), Information Science and Technology College, Dalian Maritime University, Dalian, China"],"affiliations":[{"raw_affiliation_string":"Center of Hyperspectral Imaging in Remote Sensing (CHIRS), Information Science and Technology College, Dalian Maritime University, Dalian, China","institution_ids":["https://openalex.org/I43313876"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040597347","display_name":"Zhen Xu","orcid":"https://orcid.org/0000-0002-7201-3383"},"institutions":[{"id":"https://openalex.org/I43313876","display_name":"Dalian Maritime University","ror":"https://ror.org/002b7nr53","country_code":"CN","type":"education","lineage":["https://openalex.org/I43313876"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhen Xu","raw_affiliation_strings":["Center of Hyperspectral Imaging in Remote Sensing (CHIRS), Information Science and Technology College, Dalian Maritime University, Dalian, China"],"affiliations":[{"raw_affiliation_string":"Center of Hyperspectral Imaging in Remote Sensing (CHIRS), Information Science and Technology College, Dalian Maritime University, Dalian, China","institution_ids":["https://openalex.org/I43313876"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020896207","display_name":"Ke Zheng","orcid":"https://orcid.org/0000-0002-0108-0511"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210137199","display_name":"Aerospace Information Research Institute","ror":"https://ror.org/0419fj215","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210137199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ke Zheng","raw_affiliation_strings":["Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210137199","https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5066378186","display_name":"Lianru Gao","orcid":"https://orcid.org/0000-0003-3888-8124"},"institutions":[{"id":"https://openalex.org/I4210137199","display_name":"Aerospace Information Research Institute","ror":"https://ror.org/0419fj215","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210137199"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lianru Gao","raw_affiliation_strings":["Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210137199","https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100396842"],"corresponding_institution_ids":["https://openalex.org/I43313876"],"apc_list":null,"apc_paid":null,"fwci":1.2466,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.82102719,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"2238","last_page":"2241"},"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/T13890","display_name":"Remote Sensing and Land Use","score":0.9948999881744385,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9549000263214111,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.8851481080055237},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7353720664978027},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7056061625480652},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6901868581771851},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6739544868469238},{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.6062846779823303},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.5398411750793457},{"id":"https://openalex.org/keywords/pyramid","display_name":"Pyramid (geometry)","score":0.5363553762435913},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5131781697273254},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.42552876472473145},{"id":"https://openalex.org/keywords/spatial-analysis","display_name":"Spatial analysis","score":0.4183829128742218},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.38129809498786926},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.37417125701904297},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.1719372272491455},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10725066065788269}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8851481080055237},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7353720664978027},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7056061625480652},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6901868581771851},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6739544868469238},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.6062846779823303},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.5398411750793457},{"id":"https://openalex.org/C142575187","wikidata":"https://www.wikidata.org/wiki/Q3358290","display_name":"Pyramid (geometry)","level":2,"score":0.5363553762435913},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5131781697273254},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.42552876472473145},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.4183829128742218},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.38129809498786926},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.37417125701904297},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.1719372272491455},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10725066065788269},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss47720.2021.9555010","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss47720.2021.9555010","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2627428036","display_name":null,"funder_award_id":"3132019341","funder_id":"https://openalex.org/F4320329878","funder_display_name":"Central University Basic Research Fund of China"},{"id":"https://openalex.org/G3946365887","display_name":null,"funder_award_id":"2020M680925","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"},{"id":"https://openalex.org/G5840661164","display_name":null,"funder_award_id":"2020LDE001","funder_id":"https://openalex.org/F4320321133","funder_display_name":"Chinese Academy of Sciences"}],"funders":[{"id":"https://openalex.org/F4320321133","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35"},{"id":"https://openalex.org/F4320321543","display_name":"China Postdoctoral Science Foundation","ror":"https://ror.org/0426zh255"},{"id":"https://openalex.org/F4320329878","display_name":"Central University Basic Research Fund of China","ror":null},{"id":"https://openalex.org/F4320336006","display_name":"Institute of Remote Sensing and Digital Earth","ror":"https://ror.org/02cjszf03"},{"id":"https://openalex.org/F4320338150","display_name":"Open Research Fund of Key Laboratory of Digital Earth Science","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W2340716013","https://openalex.org/W2587790406","https://openalex.org/W2808098982","https://openalex.org/W2908955282","https://openalex.org/W2941387379","https://openalex.org/W2954870938","https://openalex.org/W2966751049","https://openalex.org/W2987619624","https://openalex.org/W3105357426","https://openalex.org/W6704071466"],"related_works":["https://openalex.org/W2072166414","https://openalex.org/W3209970181","https://openalex.org/W3034375524","https://openalex.org/W4230131218","https://openalex.org/W2070598848","https://openalex.org/W2060875994","https://openalex.org/W2027399350","https://openalex.org/W2044184146","https://openalex.org/W4313014865","https://openalex.org/W2019190440"],"abstract_inverted_index":{"The":[0],"combined":[1],"use":[2,44],"of":[3,37,55,67,120],"spatial":[4],"information":[5,8],"and":[6,60,63,118],"spectral":[7],"has":[9],"been":[10,28],"widely":[11],"applied":[12],"to":[13,72],"hyperspectral":[14,31,113],"image":[15,32],"(HSI)":[16],"classification.":[17],"In":[18,70],"recent":[19],"years,":[20],"multiscale":[21],"spatial-spectral":[22],"convolutional":[23],"neural":[24],"networks":[25],"(CNN)":[26],"have":[27],"introduced":[29],"for":[30,48,93],"classification":[33,81],"(HSIC).":[34],"However,":[35],"most":[36],"HSIC":[38],"methods":[39],"based":[40],"on":[41,84,111],"CNN":[42],"mainly":[43],"patches":[45],"as":[46],"input":[47],"classifier.":[49],"This":[50,97],"may":[51],"cause":[52],"a":[53,78,89,105],"lot":[54],"redundancy":[56],"in":[57],"the":[58,65,68,116,121],"training":[59],"testing":[61],"process,":[62],"reduce":[64],"efficiency":[66,117],"model.":[69],"order":[71],"address":[73],"this":[74,85],"problem,":[75],"we":[76,87],"design":[77],"novel":[79],"image-based":[80],"framework.":[82],"Based":[83],"framework,":[86,123],"propose":[88],"multi-scale":[90],"dense":[91],"network":[92,98],"HSIs,":[94],"called":[95],"HyMSDN.":[96],"merges":[99],"features":[100],"from":[101],"different":[102],"scales":[103],"through":[104],"feature":[106],"pyramid":[107],"structure.":[108],"Experimental":[109],"results":[110],"real":[112],"dataset":[114],"verify":[115],"effectiveness":[119],"proposed":[122],"with":[124,128],"superior":[125],"performances":[126],"compared":[127],"other":[129],"related":[130],"methods.":[131]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}