{"id":"https://openalex.org/W3051556114","doi":"https://doi.org/10.1109/tgrs.2020.3014313","title":"A Lightweight Convolutional Neural Network for Hyperspectral Image Classification","display_name":"A Lightweight Convolutional Neural Network for Hyperspectral Image Classification","publication_year":2020,"publication_date":"2020-08-19","ids":{"openalex":"https://openalex.org/W3051556114","doi":"https://doi.org/10.1109/tgrs.2020.3014313","mag":"3051556114"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2020.3014313","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2020.3014313","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":true,"oa_status":"green","oa_url":"http://hdl.handle.net/10072/398179","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5035753061","display_name":"Sen Jia","orcid":"https://orcid.org/0000-0001-9742-5037"},"institutions":[{"id":"https://openalex.org/I4210104064","display_name":"Shenzhen Academy of Robotics","ror":"https://ror.org/01h027j09","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210104064"]},{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Sen Jia","raw_affiliation_strings":["Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ), Shenzhen University, Shenzhen, China","SZU Branch, Shenzhen Institute of Artificial Intelligence and Robotics for Society, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ), Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]},{"raw_affiliation_string":"SZU Branch, Shenzhen Institute of Artificial Intelligence and Robotics for Society, Shenzhen, China","institution_ids":["https://openalex.org/I4210104064"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032950508","display_name":"Zhijie Lin","orcid":"https://orcid.org/0000-0003-3671-4032"},"institutions":[{"id":"https://openalex.org/I4210104064","display_name":"Shenzhen Academy of Robotics","ror":"https://ror.org/01h027j09","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210104064"]},{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhijie Lin","raw_affiliation_strings":["Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ), Shenzhen University, Shenzhen, China","SZU Branch, Shenzhen Institute of Artificial Intelligence and Robotics for Society, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ), Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]},{"raw_affiliation_string":"SZU Branch, Shenzhen Institute of Artificial Intelligence and Robotics for Society, Shenzhen, China","institution_ids":["https://openalex.org/I4210104064"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038002446","display_name":"Meng Xu","orcid":"https://orcid.org/0000-0002-4056-7787"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]},{"id":"https://openalex.org/I4210104064","display_name":"Shenzhen Academy of Robotics","ror":"https://ror.org/01h027j09","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210104064"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Meng Xu","raw_affiliation_strings":["College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China","Guangdong Key Laboratory of Urban Informatics, Shenzhen University, Shenzhen, China","Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ), Shenzhen University, Shenzhen, China","SZU Branch, Shenzhen Institute of Artificial Intelligence and Robotics for Society, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]},{"raw_affiliation_string":"Guangdong Key Laboratory of Urban Informatics, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]},{"raw_affiliation_string":"Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ), Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]},{"raw_affiliation_string":"SZU Branch, Shenzhen Institute of Artificial Intelligence and Robotics for Society, Shenzhen, China","institution_ids":["https://openalex.org/I4210104064"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101492148","display_name":"Qiang Huang","orcid":"https://orcid.org/0000-0001-5387-6354"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]},{"id":"https://openalex.org/I4210104064","display_name":"Shenzhen Academy of Robotics","ror":"https://ror.org/01h027j09","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210104064"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiang Huang","raw_affiliation_strings":["College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China","Guangdong Key Laboratory of Urban Informatics, Shenzhen University, Shenzhen, China","Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ), Shenzhen University, Shenzhen, China","SZU Branch, Shenzhen Institute of Artificial Intelligence and Robotics for Society, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]},{"raw_affiliation_string":"Guangdong Key Laboratory of Urban Informatics, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]},{"raw_affiliation_string":"Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ), Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]},{"raw_affiliation_string":"SZU Branch, Shenzhen Institute of Artificial Intelligence and Robotics for Society, Shenzhen, China","institution_ids":["https://openalex.org/I4210104064"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100781212","display_name":"Jun Zhou","orcid":"https://orcid.org/0000-0001-5822-8233"},"institutions":[{"id":"https://openalex.org/I11701301","display_name":"Griffith University","ror":"https://ror.org/02sc3r913","country_code":"AU","type":"education","lineage":["https://openalex.org/I11701301"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Jun Zhou","raw_affiliation_strings":["School of Information and Communication Technology, Griffith University, Nathan, QLD, Australia"],"affiliations":[{"raw_affiliation_string":"School of Information and Communication Technology, Griffith University, Nathan, QLD, Australia","institution_ids":["https://openalex.org/I11701301"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024631382","display_name":"Xiuping Jia","orcid":"https://orcid.org/0000-0001-9916-6382"},"institutions":[{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]},{"id":"https://openalex.org/I188329596","display_name":"University of Canberra","ror":"https://ror.org/04s1nv328","country_code":"AU","type":"education","lineage":["https://openalex.org/I188329596"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Xiuping Jia","raw_affiliation_strings":["School of Engineering and Information Technology, University of New South Wales, Canberra, ACT, Australia"],"affiliations":[{"raw_affiliation_string":"School of Engineering and Information Technology, University of New South Wales, Canberra, ACT, Australia","institution_ids":["https://openalex.org/I188329596","https://openalex.org/I31746571"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100404067","display_name":"Qingquan Li","orcid":"https://orcid.org/0000-0002-2438-6046"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qingquan Li","raw_affiliation_strings":["Guangdong Key Laboratory of Urban Informatics, Shenzhen University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Guangdong Key Laboratory of Urban Informatics, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5035753061"],"corresponding_institution_ids":["https://openalex.org/I180726961","https://openalex.org/I4210104064"],"apc_list":null,"apc_paid":null,"fwci":9.0553,"has_fulltext":false,"cited_by_count":76,"citation_normalized_percentile":{"value":0.97967417,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"59","issue":"5","first_page":"4150","last_page":"4163"},"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":0.9951000213623047,"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":0.963100016117096,"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":0.8480793237686157},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7455340623855591},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7217203974723816},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.6182986497879028},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.616597056388855},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5667822957038879},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5519444942474365},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.5006089210510254},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.47322002053260803},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3873711824417114},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.20344218611717224}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8480793237686157},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7455340623855591},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7217203974723816},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.6182986497879028},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.616597056388855},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5667822957038879},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5519444942474365},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.5006089210510254},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.47322002053260803},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3873711824417114},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.20344218611717224}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tgrs.2020.3014313","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2020.3014313","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:research-repository.griffith.edu.au:10072/398179","is_oa":true,"landing_page_url":"http://hdl.handle.net/10072/398179","pdf_url":null,"source":{"id":"https://openalex.org/S4306402548","display_name":"Griffith Research Online (Griffith University, Queensland, Australia)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I11701301","host_organization_name":"Griffith University","host_organization_lineage":["https://openalex.org/I11701301"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Journal article"}],"best_oa_location":{"id":"pmh:oai:research-repository.griffith.edu.au:10072/398179","is_oa":true,"landing_page_url":"http://hdl.handle.net/10072/398179","pdf_url":null,"source":{"id":"https://openalex.org/S4306402548","display_name":"Griffith Research Online (Griffith University, Queensland, Australia)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I11701301","host_organization_name":"Griffith University","host_organization_lineage":["https://openalex.org/I11701301"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Journal article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1688454784","display_name":null,"funder_award_id":"JCYJ20180305124802421","funder_id":"https://openalex.org/F4320329801","funder_display_name":"Shenzhen Research and Development Program"},{"id":"https://openalex.org/G2264764757","display_name":null,"funder_award_id":"61901278","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3638989402","display_name":null,"funder_award_id":"41971300","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5182593556","display_name":null,"funder_award_id":"JCYJ20180305125902403","funder_id":"https://openalex.org/F4320329801","funder_display_name":"Shenzhen Research and Development Program"},{"id":"https://openalex.org/G5538422374","display_name":null,"funder_award_id":"61671307","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"},{"id":"https://openalex.org/F4320329801","display_name":"Shenzhen Research and Development Program","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":74,"referenced_works":["https://openalex.org/W248389711","https://openalex.org/W1499864241","https://openalex.org/W1521436688","https://openalex.org/W1616262590","https://openalex.org/W1799366690","https://openalex.org/W1932531222","https://openalex.org/W1939429412","https://openalex.org/W1994605595","https://openalex.org/W1998030734","https://openalex.org/W2000008842","https://openalex.org/W2004104348","https://openalex.org/W2006419537","https://openalex.org/W2053186076","https://openalex.org/W2053512934","https://openalex.org/W2056067618","https://openalex.org/W2097308346","https://openalex.org/W2103094532","https://openalex.org/W2111975408","https://openalex.org/W2112796928","https://openalex.org/W2126447858","https://openalex.org/W2130942839","https://openalex.org/W2131438174","https://openalex.org/W2131725398","https://openalex.org/W2144151128","https://openalex.org/W2161815745","https://openalex.org/W2166923144","https://openalex.org/W2314785379","https://openalex.org/W2325687635","https://openalex.org/W2341894713","https://openalex.org/W2345118402","https://openalex.org/W2346557146","https://openalex.org/W2518897583","https://openalex.org/W2544692362","https://openalex.org/W2572303978","https://openalex.org/W2573524522","https://openalex.org/W2580081062","https://openalex.org/W2595902385","https://openalex.org/W2598997103","https://openalex.org/W2603422184","https://openalex.org/W2765622256","https://openalex.org/W2768975974","https://openalex.org/W2770315464","https://openalex.org/W2773022682","https://openalex.org/W2782356138","https://openalex.org/W2789290064","https://openalex.org/W2791006446","https://openalex.org/W2800371750","https://openalex.org/W2888715336","https://openalex.org/W2896972575","https://openalex.org/W2898204262","https://openalex.org/W2900116731","https://openalex.org/W2909724221","https://openalex.org/W2922638023","https://openalex.org/W2941387379","https://openalex.org/W2942454403","https://openalex.org/W2948256530","https://openalex.org/W2953547566","https://openalex.org/W2954497554","https://openalex.org/W2964086062","https://openalex.org/W3003552243","https://openalex.org/W3003571776","https://openalex.org/W3021010628","https://openalex.org/W3031768327","https://openalex.org/W3100011500","https://openalex.org/W3102431071","https://openalex.org/W4300952079","https://openalex.org/W6629930100","https://openalex.org/W6638444622","https://openalex.org/W6648864150","https://openalex.org/W6650461377","https://openalex.org/W6679436768","https://openalex.org/W6760560674","https://openalex.org/W6764922716","https://openalex.org/W6776868830"],"related_works":["https://openalex.org/W1574414179","https://openalex.org/W4362597605","https://openalex.org/W4297676672","https://openalex.org/W4281702477","https://openalex.org/W2922073769","https://openalex.org/W4378510483","https://openalex.org/W2490526372","https://openalex.org/W2132083814","https://openalex.org/W3128011703","https://openalex.org/W2565656575"],"abstract_inverted_index":{"In":[0,103],"the":[1,12,17,48,53,75,79,96,100,121,138,143,149,154,169,185,193,206,228,237,253,270,278],"hyperspectral":[2,32,71,115,264,284],"image,":[3],"each":[4,257],"pixel":[5],"corresponds":[6],"to":[7,82,91,118,136,167,191,251],"a":[8,41,106,159,173,217,246],"small":[9,42,122],"area":[10],"on":[11,261],"Earth's":[13],"surface":[14],"and":[15,40,85,142,184,230,243,280,288,295],"represents":[16],"intrinsic":[18,229],"characteristic":[19],"of":[20,28,99,151,179,256],"objects,":[21],"which":[22,58,223],"can":[23,89],"be":[24,47,83],"applied":[25,62],"for":[26,70,114,283],"recognition":[27],"land":[29],"covers.":[30],"Nevertheless,":[31],"image":[33,72,116,265,285],"processing":[34],"should":[35],"face":[36],"some":[37],"critical":[38],"issues,":[39],"sample":[43,123],"set":[44,124],"problem":[45],"may":[46],"most":[49],"challenging":[50],"one":[51],"in":[52,63,153,276],"research.":[54],"Deep":[55],"learning":[56],"(DL),":[57],"has":[59,66],"successfully":[60],"been":[61,68],"many":[64],"fields,":[65],"also":[67],"introduced":[69],"classification.":[73],"However,":[74],"large":[76],"gap":[77],"between":[78],"massive":[80],"parameters":[81,152,180],"tuned":[84],"limited":[86,299],"labeled":[87,300],"samples":[88],"lead":[90],"overfitting":[92],"scenario,":[93],"inevitably":[94],"deteriorating":[95],"generalization":[97],"ability":[98],"DL":[101,156],"model.":[102,157],"this":[104],"article,":[105],"lightweight":[107],"convolutional":[108],"neural":[109],"network":[110],"(LWCNN)":[111],"is":[112,133,164,181,188,274],"proposed":[113],"classification":[117,286],"mainly":[119],"tackle":[120],"problem.":[125],"Especially,":[126],"spatial-spectral":[127,140],"Schroedinger":[128],"eigenmaps":[129],"(SSSE)":[130],"feature":[131,207],"extraction":[132],"first":[134],"adopted":[135],"obtain":[137,192],"joint":[139],"information,":[141],"compressed":[144],"dimensionality":[145],"could":[146,198,224],"significantly":[147],"reduce":[148],"number":[150,178],"following":[155],"Second,":[158],"dual-scale":[160],"convolution":[161],"(DSC)":[162],"module":[163],"carefully":[165],"designed":[166],"address":[168],"SSSE":[170],"features":[171,239],"from":[172,202,209],"1-D":[174],"vector":[175],"viewpoint":[176],"(the":[177],"further":[182],"decreased),":[183],"DSC":[186,211,234],"procedure":[187],"successively":[189],"employed":[190],"hierarchical":[194],"structure":[195],"description":[196],"that":[197,269],"represent":[199],"data":[200,266],"distribution":[201],"different":[203],"aspects.":[204],"Subsequently,":[205],"vectors":[208],"all":[210],"layers":[212],"are":[213,240],"separately":[214],"filtered":[215,238],"by":[216],"new":[218],"bichannel":[219],"fusion":[220],"(BCF)":[221],"module,":[222],"well":[225],"encode":[226],"both":[227,277],"contextual":[231],"information":[232],"inside":[233],"features.":[235],"Finally,":[236],"concatenated":[241],"together":[242],"imported":[244],"into":[245],"global":[247],"average":[248],"pooling":[249],"classifier":[250],"achieve":[252],"predicted":[254],"probability":[255],"category.":[258],"Experimental":[259],"results":[260],"three":[262],"famous":[263],"sets":[267],"illustrate":[268],"developed":[271],"LWCNN":[272],"approach":[273],"advantageous":[275],"efficiency":[279],"robustness":[281],"sides":[282],"tasks":[287],"outperforms":[289],"other":[290],"state-of-the-art":[291],"methods":[292],"(both":[293],"traditional-based":[294],"DL-based)":[296],"with":[297],"very":[298],"samples.":[301]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":15},{"year":2023,"cited_by_count":20},{"year":2022,"cited_by_count":20},{"year":2021,"cited_by_count":8}],"updated_date":"2026-02-27T16:54:17.756197","created_date":"2025-10-10T00:00:00"}
