{"id":"https://openalex.org/W3129961032","doi":"https://doi.org/10.1109/igarss39084.2020.9323359","title":"Dimensionality Reduction Using 3D Residual Autoencoder for Hyperspectral Image Classification","display_name":"Dimensionality Reduction Using 3D Residual Autoencoder for Hyperspectral Image Classification","publication_year":2020,"publication_date":"2020-09-26","ids":{"openalex":"https://openalex.org/W3129961032","doi":"https://doi.org/10.1109/igarss39084.2020.9323359","mag":"3129961032"},"language":"en","primary_location":{"id":"doi:10.1109/igarss39084.2020.9323359","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss39084.2020.9323359","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2020 - 2020 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/A5009437784","display_name":"Shivam Pande","orcid":"https://orcid.org/0000-0003-2020-9306"},"institutions":[{"id":"https://openalex.org/I162827531","display_name":"Indian Institute of Technology Bombay","ror":"https://ror.org/02qyf5152","country_code":"IN","type":"education","lineage":["https://openalex.org/I162827531"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Shivam Pande","raw_affiliation_strings":["Centre of Studies in Resources Engineering, Indian Institute of Technology Bombay, India"],"affiliations":[{"raw_affiliation_string":"Centre of Studies in Resources Engineering, Indian Institute of Technology Bombay, India","institution_ids":["https://openalex.org/I162827531"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020786167","display_name":"Biplab Banerjee","orcid":"https://orcid.org/0000-0001-8371-8138"},"institutions":[{"id":"https://openalex.org/I162827531","display_name":"Indian Institute of Technology Bombay","ror":"https://ror.org/02qyf5152","country_code":"IN","type":"education","lineage":["https://openalex.org/I162827531"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Biplab Banerjee","raw_affiliation_strings":["Centre of Studies in Resources Engineering, Indian Institute of Technology Bombay, India"],"affiliations":[{"raw_affiliation_string":"Centre of Studies in Resources Engineering, Indian Institute of Technology Bombay, India","institution_ids":["https://openalex.org/I162827531"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5009437784"],"corresponding_institution_ids":["https://openalex.org/I162827531"],"apc_list":null,"apc_paid":null,"fwci":1.1319,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.84623739,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"2029","last_page":"2032"},"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":0.9937999844551086,"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":0.9140803813934326},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.9062108993530273},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.7531957030296326},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6837315559387207},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6621925830841064},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6167557239532471},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.6069356203079224},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.5513446927070618},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.5206484198570251},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.46685534715652466},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2193027138710022},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.1631961166858673}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.9140803813934326},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.9062108993530273},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.7531957030296326},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6837315559387207},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6621925830841064},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6167557239532471},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.6069356203079224},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.5513446927070618},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.5206484198570251},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.46685534715652466},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2193027138710022},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.1631961166858673},{"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/igarss39084.2020.9323359","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss39084.2020.9323359","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Life in Land","score":0.699999988079071,"id":"https://metadata.un.org/sdg/15"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W1990895816","https://openalex.org/W2136251662","https://openalex.org/W2157621128","https://openalex.org/W2179290474","https://openalex.org/W2194775991","https://openalex.org/W2602031553","https://openalex.org/W2903382683","https://openalex.org/W2940678725","https://openalex.org/W2944248482"],"related_works":["https://openalex.org/W4310873165","https://openalex.org/W2132083814","https://openalex.org/W2292979300","https://openalex.org/W2355395139","https://openalex.org/W4285596704","https://openalex.org/W1995622179","https://openalex.org/W4391160746","https://openalex.org/W1484111231","https://openalex.org/W1552543208","https://openalex.org/W2074396517"],"abstract_inverted_index":{"Hyperspectral":[0],"images":[1],"(HSIs)":[2],"are":[3,108],"actively":[4],"used":[5,109],"for":[6],"land-use/land-cover":[7],"classification.":[8,144],"However,":[9],"HSIs":[10],"suffer":[11],"from":[12],"the":[13,38,76,88,100,112,116,137],"problem":[14,47],"of":[15,25,28,48,102],"high":[16,19],"dimensionality":[17],"and":[18,71,132,136],"spectral-spatial":[20,89],"variability":[21],"leading":[22],"to":[23,36,74,80,110],"requirement":[24],"large":[26],"number":[27],"training":[29],"samples.":[30],"Deep":[31],"learning":[32],"offers":[33],"several":[34],"approaches":[35],"handle":[37,87],"aforementioned":[39],"problems":[40],"but":[41],"is":[42,118,127],"limited":[43],"with":[44],"its":[45,141],"own":[46],"vanishing":[49,103],"gradient":[50],"that":[51,67],"creeps":[52],"in":[53,120,143],"deeper":[54],"networks":[55],"(especially":[56],"CNNs).":[57],"In":[58],"this":[59],"paper,":[60],"we":[61],"propose":[62],"an":[63,95],"autoencoder":[64],"(3D":[65],"ResAE)":[66],"uses":[68],"3D":[69,84,106],"convolutions":[70,85],"residual":[72,92],"blocks":[73],"project":[75],"high-dimensional":[77],"HSI":[78],"features":[79],"a":[81,121],"low-dimensional":[82],"space.":[83],"effectively":[86],"characteristics":[90],"whereas,":[91],"block":[93],"adds":[94],"identity":[96],"mapping,":[97],"thereby":[98],"tackling":[99],"issue":[101],"gradient.":[104],"Furthermore,":[105],"deconvolutions":[107],"reconstruct":[111],"original":[113],"features,":[114],"while":[115],"network":[117],"trained":[119],"semi-supervised":[122],"manner.":[123],"Our":[124],"proposed":[125],"method":[126],"tested":[128],"on":[129],"Indian":[130],"pines":[131],"Salinas":[133],"hyperspectral":[134],"datasets":[135],"results":[138],"clearly":[139],"demonstrate":[140],"effectiveness":[142]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}