{"id":"https://openalex.org/W3032070687","doi":"https://doi.org/10.1109/jstars.2020.2995445","title":"Adaptive Residual Convolutional Neural Network for Hyperspectral Image Classification","display_name":"Adaptive Residual Convolutional Neural Network for Hyperspectral Image Classification","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3032070687","doi":"https://doi.org/10.1109/jstars.2020.2995445","mag":"3032070687"},"language":"en","primary_location":{"id":"doi:10.1109/jstars.2020.2995445","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2020.2995445","pdf_url":"https://ieeexplore.ieee.org/ielx7/4609443/8994817/09102351.pdf","source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/4609443/8994817/09102351.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101829389","display_name":"Hong Huang","orcid":"https://orcid.org/0000-0002-7377-3077"},"institutions":[{"id":"https://openalex.org/I50632499","display_name":"Chongqing University of Technology","ror":"https://ror.org/04vgbd477","country_code":"CN","type":"education","lineage":["https://openalex.org/I50632499"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hong Huang","raw_affiliation_strings":["Key Laboratory of Optoelectronic Technology and Systems of the Education Ministry of China, Chongqing University, Chongqing, China","ORCiD"],"raw_orcid":"https://orcid.org/0000-0002-7377-3077","affiliations":[{"raw_affiliation_string":"Key Laboratory of Optoelectronic Technology and Systems of the Education Ministry of China, Chongqing University, Chongqing, China","institution_ids":["https://openalex.org/I50632499"]},{"raw_affiliation_string":"ORCiD","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001042029","display_name":"Chunyu Pu","orcid":null},"institutions":[{"id":"https://openalex.org/I50632499","display_name":"Chongqing University of Technology","ror":"https://ror.org/04vgbd477","country_code":"CN","type":"education","lineage":["https://openalex.org/I50632499"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chunyu Pu","raw_affiliation_strings":["Key Laboratory of Optoelectronic Technology and Systems of the Education Ministry of China, Chongqing University, Chongqing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Optoelectronic Technology and Systems of the Education Ministry of China, Chongqing University, Chongqing, China","institution_ids":["https://openalex.org/I50632499"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101512990","display_name":"Yuan Li","orcid":"https://orcid.org/0009-0006-9301-9369"},"institutions":[{"id":"https://openalex.org/I50632499","display_name":"Chongqing University of Technology","ror":"https://ror.org/04vgbd477","country_code":"CN","type":"education","lineage":["https://openalex.org/I50632499"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuan Li","raw_affiliation_strings":["Key Laboratory of Optoelectronic Technology and Systems of the Education Ministry of China, Chongqing University, Chongqing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Optoelectronic Technology and Systems of the Education Ministry of China, Chongqing University, Chongqing, China","institution_ids":["https://openalex.org/I50632499"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5033398332","display_name":"Yule Duan","orcid":"https://orcid.org/0000-0002-2505-8730"},"institutions":[{"id":"https://openalex.org/I50632499","display_name":"Chongqing University of Technology","ror":"https://ror.org/04vgbd477","country_code":"CN","type":"education","lineage":["https://openalex.org/I50632499"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yule Duan","raw_affiliation_strings":["Key Laboratory of Optoelectronic Technology and Systems of the Education Ministry of China, Chongqing University, Chongqing, China","ORCiD"],"raw_orcid":"https://orcid.org/0000-0002-2505-8730","affiliations":[{"raw_affiliation_string":"Key Laboratory of Optoelectronic Technology and Systems of the Education Ministry of China, Chongqing University, Chongqing, China","institution_ids":["https://openalex.org/I50632499"]},{"raw_affiliation_string":"ORCiD","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I50632499"],"apc_list":{"value":1250,"currency":"USD","value_usd":1250},"apc_paid":{"value":1250,"currency":"USD","value_usd":1250},"fwci":4.9161,"has_fulltext":true,"cited_by_count":36,"citation_normalized_percentile":{"value":0.9560917,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"13","issue":null,"first_page":"2520","last_page":"2531"},"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":0.9965000152587891,"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":0.9846000075340271,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7718710899353027},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7647586464881897},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.753774881362915},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.7318784594535828},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7155078649520874},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6684371829032898},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.6282421350479126},{"id":"https://openalex.org/keywords/normalization","display_name":"Normalization (sociology)","score":0.5656537413597107},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5556429028511047},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.5383718013763428},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.49238574504852295},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.46152442693710327},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.45444804430007935},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.33084481954574585},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3171432614326477},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.1401124894618988},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.08303084969520569}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7718710899353027},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7647586464881897},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.753774881362915},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.7318784594535828},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7155078649520874},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6684371829032898},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.6282421350479126},{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.5656537413597107},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5556429028511047},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.5383718013763428},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.49238574504852295},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.46152442693710327},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.45444804430007935},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33084481954574585},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3171432614326477},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1401124894618988},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.08303084969520569},{"id":"https://openalex.org/C19165224","wikidata":"https://www.wikidata.org/wiki/Q23404","display_name":"Anthropology","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/jstars.2020.2995445","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2020.2995445","pdf_url":"https://ieeexplore.ieee.org/ielx7/4609443/8994817/09102351.pdf","source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:e59ff4a4b4444f9d949b0b35470de440","is_oa":true,"landing_page_url":"https://doaj.org/article/e59ff4a4b4444f9d949b0b35470de440","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 13, Pp 2520-2531 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/jstars.2020.2995445","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2020.2995445","pdf_url":"https://ieeexplore.ieee.org/ielx7/4609443/8994817/09102351.pdf","source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.7599999904632568,"display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G103021876","display_name":null,"funder_award_id":"CYB18048","funder_id":"https://openalex.org/F4320321135","funder_display_name":"Chongqing University"}],"funders":[{"id":"https://openalex.org/F4320321135","display_name":"Chongqing University","ror":"https://ror.org/023rhb549"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3032070687.pdf","grobid_xml":"https://content.openalex.org/works/W3032070687.grobid-xml"},"referenced_works_count":50,"referenced_works":["https://openalex.org/W1590594428","https://openalex.org/W1897878572","https://openalex.org/W1950365613","https://openalex.org/W1979730959","https://openalex.org/W1998030734","https://openalex.org/W2019188302","https://openalex.org/W2029316659","https://openalex.org/W2031510368","https://openalex.org/W2036109700","https://openalex.org/W2053852479","https://openalex.org/W2063385051","https://openalex.org/W2072187267","https://openalex.org/W2087263574","https://openalex.org/W2100285320","https://openalex.org/W2145934166","https://openalex.org/W2169500530","https://openalex.org/W2346155541","https://openalex.org/W2406440244","https://openalex.org/W2412588858","https://openalex.org/W2500751094","https://openalex.org/W2572303978","https://openalex.org/W2576298706","https://openalex.org/W2577238056","https://openalex.org/W2614326984","https://openalex.org/W2738447277","https://openalex.org/W2752782242","https://openalex.org/W2764276316","https://openalex.org/W2764299699","https://openalex.org/W2772452219","https://openalex.org/W2781621993","https://openalex.org/W2783165089","https://openalex.org/W2801324747","https://openalex.org/W2808979303","https://openalex.org/W2889861425","https://openalex.org/W2894165434","https://openalex.org/W2902788350","https://openalex.org/W2914429466","https://openalex.org/W2937638900","https://openalex.org/W2937675449","https://openalex.org/W2940678725","https://openalex.org/W2942170965","https://openalex.org/W2950266692","https://openalex.org/W2962702700","https://openalex.org/W2963420686","https://openalex.org/W2963796061","https://openalex.org/W2965318645","https://openalex.org/W2968460295","https://openalex.org/W2991488782","https://openalex.org/W3105005050","https://openalex.org/W3105553032"],"related_works":["https://openalex.org/W1574414179","https://openalex.org/W3040691452","https://openalex.org/W3208297503","https://openalex.org/W2761785940","https://openalex.org/W3119773509","https://openalex.org/W2889153461","https://openalex.org/W2964117661","https://openalex.org/W4388405611","https://openalex.org/W2619127353","https://openalex.org/W3128011703"],"abstract_inverted_index":{"In":[0,25,100],"this":[1,26],"article,":[2],"we":[3],"designed":[4],"an":[5,53,92,121],"adaptive":[6],"residual":[7,82],"convolutional":[8,88,149],"neural":[9],"network":[10],"(ARCNN)":[11],"that":[12,58],"takes":[13],"raw":[14],"hyperspectral":[15],"image":[16],"(HSI)":[17],"cubes":[18],"as":[19],"input":[20],"data":[21],"for":[22,118],"land-cover":[23],"classification.":[24],"network,":[27],"spectral":[28,42],"and":[29,44,67,73,112,124,143,166],"spatial":[30,45],"feature":[31,126],"extraction":[32],"blocks":[33,83],"are":[34,129,145],"explored":[35],"to":[36,102,131,151,162,170],"learn":[37],"discriminative":[38,164],"features":[39],"from":[40],"abundant":[41],"information":[43],"contexts":[46],"in":[47,78],"HSIs.":[48,79],"The":[49],"proposed":[50],"ARCNN":[51,158,185],"is":[52,168],"end-to-end":[54],"deep":[55,64],"learning":[56,65,154],"framework":[57],"alleviates":[59],"the":[60,71,81,104,133,136,153,157,181,184],"declining-accuracy":[61],"phenomenon":[62],"of":[63,75,98,107,115,135,183],"models,":[66],"it":[68,167],"also":[69],"ranks":[70],"correlation":[72],"importance":[74],"each":[76],"band":[77],"Furthermore,":[80],"connect":[84],"every":[85,148],"other":[86],"3-D":[87],"layer":[89,150],"by":[90],"using":[91],"identity":[93],"mapping,":[94],"which":[95],"facilitates":[96],"backpropagation":[97],"gradients.":[99],"order":[101],"address":[103],"common":[105],"issue":[106],"imbalance":[108],"between":[109],"high":[110],"dimensionality":[111],"limited":[113],"availability":[114],"training":[116],"samples":[117],"HSI":[119,178],"classification,":[120],"attention":[122],"mechanism":[123],"a":[125],"fusion":[127],"block":[128],"investigated":[130],"improve":[132],"performance":[134],"ARCNN.":[137],"Finally,":[138],"some":[139,187],"strategies,":[140],"batch":[141],"normalization":[142],"dropout,":[144],"imposed":[146],"on":[147,175],"regularize":[152],"process.":[155],"Therefore,":[156],"method":[159],"brings":[160],"benefits":[161],"extract":[163],"features,":[165],"easier":[169],"avoid":[171],"overfitting.":[172],"Experimental":[173],"results":[174],"three":[176],"public":[177],"datasets":[179],"demonstrate":[180],"effectiveness":[182],"over":[186],"state-of-the-art":[188],"methods.":[189]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":9},{"year":2021,"cited_by_count":10},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
