{"id":"https://openalex.org/W4323338610","doi":"https://doi.org/10.1109/access.2023.3252888","title":"Depth Separable-CNN for Improved Spectral Super-Resolution","display_name":"Depth Separable-CNN for Improved Spectral Super-Resolution","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4323338610","doi":"https://doi.org/10.1109/access.2023.3252888"},"language":"en","primary_location":{"id":"doi:10.1109/access.2023.3252888","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3252888","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10058939.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10058939.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5084664959","display_name":"Sadia Hussain","orcid":"https://orcid.org/0000-0002-5507-1063"},"institutions":[{"id":"https://openalex.org/I68891433","display_name":"Indian Institute of Technology Delhi","ror":"https://ror.org/049tgcd06","country_code":"IN","type":"education","lineage":["https://openalex.org/I68891433"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Sadia Hussain","raw_affiliation_strings":["Bharti School of Telecommunications Technology and Management (BSTTM), Indian Institute of Technology Delhi, Hauz Khas, Delhi, India","Department of Electrical Engineering, Indian Institute of Technology Delhi, Hauz Khas"],"raw_orcid":"https://orcid.org/0000-0002-5507-1063","affiliations":[{"raw_affiliation_string":"Bharti School of Telecommunications Technology and Management (BSTTM), Indian Institute of Technology Delhi, Hauz Khas, Delhi, India","institution_ids":["https://openalex.org/I68891433"]},{"raw_affiliation_string":"Department of Electrical Engineering, Indian Institute of Technology Delhi, Hauz Khas","institution_ids":["https://openalex.org/I68891433"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5066116024","display_name":"Brejesh Lall","orcid":"https://orcid.org/0000-0003-2677-3071"},"institutions":[{"id":"https://openalex.org/I68891433","display_name":"Indian Institute of Technology Delhi","ror":"https://ror.org/049tgcd06","country_code":"IN","type":"education","lineage":["https://openalex.org/I68891433"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Brejesh Lall","raw_affiliation_strings":["Bharti School of Telecommunications Technology and Management (BSTTM), Indian Institute of Technology Delhi, Hauz Khas, Delhi, India"],"raw_orcid":"https://orcid.org/0000-0003-2677-3071","affiliations":[{"raw_affiliation_string":"Bharti School of Telecommunications Technology and Management (BSTTM), Indian Institute of Technology Delhi, Hauz Khas, Delhi, India","institution_ids":["https://openalex.org/I68891433"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5084664959"],"corresponding_institution_ids":["https://openalex.org/I68891433"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.2127,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.45654602,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":"11","issue":null,"first_page":"23063","last_page":"23072"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9998000264167786,"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"}},{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.9998000264167786,"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"}},{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9998000264167786,"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":0.7616151571273804},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.6915866136550903},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6584054827690125},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6046921014785767},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.6045327186584473},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.6026853919029236},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5833832025527954},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5489417314529419},{"id":"https://openalex.org/keywords/separable-space","display_name":"Separable space","score":0.5054078102111816},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.47085991501808167},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.4370499849319458},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.43360620737075806},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.28133559226989746},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.22782817482948303}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.7616151571273804},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.6915866136550903},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6584054827690125},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6046921014785767},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.6045327186584473},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.6026853919029236},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5833832025527954},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5489417314529419},{"id":"https://openalex.org/C70710897","wikidata":"https://www.wikidata.org/wiki/Q680081","display_name":"Separable space","level":2,"score":0.5054078102111816},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.47085991501808167},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.4370499849319458},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.43360620737075806},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.28133559226989746},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.22782817482948303},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2023.3252888","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3252888","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10058939.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:956fcbb9ac99451bb139a4e36f58d76d","is_oa":true,"landing_page_url":"https://doaj.org/article/956fcbb9ac99451bb139a4e36f58d76d","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 Access, Vol 11, Pp 23063-23072 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2023.3252888","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3252888","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10058939.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4323338610.pdf","grobid_xml":"https://content.openalex.org/works/W4323338610.grobid-xml"},"referenced_works_count":49,"referenced_works":["https://openalex.org/W935139217","https://openalex.org/W1550575628","https://openalex.org/W1885185971","https://openalex.org/W1901129140","https://openalex.org/W1964248402","https://openalex.org/W1971319412","https://openalex.org/W1977791453","https://openalex.org/W1984864470","https://openalex.org/W1992653101","https://openalex.org/W1997201895","https://openalex.org/W2002604566","https://openalex.org/W2012946078","https://openalex.org/W2044011870","https://openalex.org/W2048976066","https://openalex.org/W2060022367","https://openalex.org/W2100109944","https://openalex.org/W2200474412","https://openalex.org/W2221625691","https://openalex.org/W2242218935","https://openalex.org/W2327302159","https://openalex.org/W2520430674","https://openalex.org/W2559597482","https://openalex.org/W2604824122","https://openalex.org/W2752782242","https://openalex.org/W2753685993","https://openalex.org/W2765366036","https://openalex.org/W2766101120","https://openalex.org/W2768203249","https://openalex.org/W2792111852","https://openalex.org/W2793272303","https://openalex.org/W2848020186","https://openalex.org/W2893739000","https://openalex.org/W2899663614","https://openalex.org/W2902415664","https://openalex.org/W2914997670","https://openalex.org/W2963923251","https://openalex.org/W2963947695","https://openalex.org/W2997011911","https://openalex.org/W2997797376","https://openalex.org/W3036200672","https://openalex.org/W3043719198","https://openalex.org/W3099189289","https://openalex.org/W3099608030","https://openalex.org/W3104313739","https://openalex.org/W3130282602","https://openalex.org/W4206819352","https://openalex.org/W6704241340","https://openalex.org/W6736270120","https://openalex.org/W6755977528"],"related_works":["https://openalex.org/W3158431807","https://openalex.org/W2530952058","https://openalex.org/W2582836483","https://openalex.org/W4299366318","https://openalex.org/W4297580547","https://openalex.org/W2951583185","https://openalex.org/W2543396502","https://openalex.org/W4308155352","https://openalex.org/W4386858688","https://openalex.org/W3034421924"],"abstract_inverted_index":{"Hyperspectral":[0,153],"Image":[1],"reconstruction":[2],"from":[3,155],"RGB":[4,156],"images":[5,15],"is":[6,34],"a":[7,76,86,90,137],"low-cost":[8],"and":[9,25,110,123,146,179],"convenient":[10],"alternative":[11],"to":[12,141,169],"acquiring":[13],"hyperspectral":[14,31],"directly.":[16],"The":[17,100,129],"challenge":[18],"in":[19,119,136,149],"estimating":[20],"the":[21,30,38,45,97,180,184],"spectral":[22,98,127],"response":[23],"function":[24],"using":[26],"it":[27],"for":[28,44],"generating":[29],"image":[32],"data":[33,154],"addressed":[35],"effectively":[36],"by":[37,85,94],"use":[39,131],"of":[40,75,78,89,132,186],"Deep":[41,47,64],"convolutional":[42],"networks":[43,62],"task.":[46],"networks,":[48],"however,":[49],"involve":[50],"expensive":[51],"convolutions.":[52],"To":[53],"address":[54],"this":[55,159],"problem,":[56],"we":[57,161],"have":[58,162],"adapted":[59],"deep":[60,172],"convolution":[61,66,83,92,95,134],"into":[63],"Separable":[65],"networks.":[67],"We":[68],"propose":[69],"an":[70],"isotropic":[71],"network":[72],"which":[73],"consists":[74],"cascade":[77],"blocks":[79],"implementing":[80],"depth":[81],"separable":[82],"constructed":[84],"series":[87],"combination":[88],"spatial":[91,121],"followed":[93],"along":[96],"domain.":[99],"two":[101],"sub-blocks":[102],"are":[103],"termed":[104],"as":[105],"<italic":[106,111],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[107,112],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">intra-channel</i>":[108],"sub-block":[109,114,117,125],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">intra-pixel</i>":[113],"respectively.":[115],"Intra-channel":[116],"helps":[118,148],"capturing":[120],"correlation":[122],"intra-pixel":[124],"captures":[126],"correlations.":[128],"explicit":[130],"spectral-domain":[133],"results":[135],"more":[138,151],"direct":[139],"approach":[140],"interpolating":[142],"information":[143],"across":[144],"bands":[145],"hence":[147],"obtaining":[150],"accurate":[152],"images.":[157],"In":[158],"study":[160,182],"conducted":[163],"experiments":[164],"on":[165],"three":[166],"benchmark":[167],"datasets":[168],"show":[170],"that":[171],"separable-CNN":[173],"achieves":[174],"better":[175],"accuracy.":[176],"These":[177],"result":[178],"ablation":[181],"demonstrate":[183],"superiority":[185],"our":[187],"technique.":[188]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}