{"id":"https://openalex.org/W3089820912","doi":"https://doi.org/10.1109/tgrs.2020.3024730","title":"FLOP-Reduction Through Memory Allocations Within CNN for Hyperspectral Image Classification","display_name":"FLOP-Reduction Through Memory Allocations Within CNN for Hyperspectral Image Classification","publication_year":2020,"publication_date":"2020-09-29","ids":{"openalex":"https://openalex.org/W3089820912","doi":"https://doi.org/10.1109/tgrs.2020.3024730","mag":"3089820912"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2020.3024730","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2020.3024730","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":"https://zenodo.org/record/8071073","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5046123228","display_name":"Mercedes E. Paoletti","orcid":"https://orcid.org/0000-0003-1030-3729"},"institutions":[{"id":"https://openalex.org/I80606768","display_name":"Universidad de Extremadura","ror":"https://ror.org/0174shg90","country_code":"ES","type":"education","lineage":["https://openalex.org/I80606768"]}],"countries":["ES"],"is_corresponding":true,"raw_author_name":"Mercedes E. Paoletti","raw_affiliation_strings":["Department of Technology of Computers and Communications, Hyperspectral Computing Laboratory, Escuela Polit\u00e9cnica, University of Extremadura, C\u00e1ceres, Spain"],"affiliations":[{"raw_affiliation_string":"Department of Technology of Computers and Communications, Hyperspectral Computing Laboratory, Escuela Polit\u00e9cnica, University of Extremadura, C\u00e1ceres, Spain","institution_ids":["https://openalex.org/I80606768"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039673511","display_name":"Juan M. Haut","orcid":"https://orcid.org/0000-0001-6701-961X"},"institutions":[{"id":"https://openalex.org/I80606768","display_name":"Universidad de Extremadura","ror":"https://ror.org/0174shg90","country_code":"ES","type":"education","lineage":["https://openalex.org/I80606768"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Juan M. Haut","raw_affiliation_strings":["Department of Technology of Computers and Communications, Hyperspectral Computing Laboratory, Escuela Polit\u00e9cnica, University of Extremadura, C\u00e1ceres, Spain"],"affiliations":[{"raw_affiliation_string":"Department of Technology of Computers and Communications, Hyperspectral Computing Laboratory, Escuela Polit\u00e9cnica, University of Extremadura, C\u00e1ceres, Spain","institution_ids":["https://openalex.org/I80606768"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033046838","display_name":"Xuanwen Tao","orcid":"https://orcid.org/0000-0003-1093-0079"},"institutions":[{"id":"https://openalex.org/I80606768","display_name":"Universidad de Extremadura","ror":"https://ror.org/0174shg90","country_code":"ES","type":"education","lineage":["https://openalex.org/I80606768"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Xuanwen Tao","raw_affiliation_strings":["Department of Technology of Computers and Communications, Hyperspectral Computing Laboratory, Escuela Polit\u00e9cnica, University of Extremadura, C\u00e1ceres, Spain"],"affiliations":[{"raw_affiliation_string":"Department of Technology of Computers and Communications, Hyperspectral Computing Laboratory, Escuela Polit\u00e9cnica, University of Extremadura, C\u00e1ceres, Spain","institution_ids":["https://openalex.org/I80606768"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010624980","display_name":"Javier Plaza","orcid":"https://orcid.org/0000-0002-2384-9141"},"institutions":[{"id":"https://openalex.org/I80606768","display_name":"Universidad de Extremadura","ror":"https://ror.org/0174shg90","country_code":"ES","type":"education","lineage":["https://openalex.org/I80606768"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Javier Plaza","raw_affiliation_strings":["Department of Technology of Computers and Communications, Hyperspectral Computing Laboratory, Escuela Polit\u00e9cnica, University of Extremadura, C\u00e1ceres, Spain"],"affiliations":[{"raw_affiliation_string":"Department of Technology of Computers and Communications, Hyperspectral Computing Laboratory, Escuela Polit\u00e9cnica, University of Extremadura, C\u00e1ceres, Spain","institution_ids":["https://openalex.org/I80606768"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054292278","display_name":"Antonio Plaza","orcid":"https://orcid.org/0000-0002-9613-1659"},"institutions":[{"id":"https://openalex.org/I80606768","display_name":"Universidad de Extremadura","ror":"https://ror.org/0174shg90","country_code":"ES","type":"education","lineage":["https://openalex.org/I80606768"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Antonio Plaza","raw_affiliation_strings":["Department of Technology of Computers and Communications, Hyperspectral Computing Laboratory, Escuela Polit\u00e9cnica, University of Extremadura, C\u00e1ceres, Spain"],"affiliations":[{"raw_affiliation_string":"Department of Technology of Computers and Communications, Hyperspectral Computing Laboratory, Escuela Polit\u00e9cnica, University of Extremadura, C\u00e1ceres, Spain","institution_ids":["https://openalex.org/I80606768"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5046123228"],"corresponding_institution_ids":["https://openalex.org/I80606768"],"apc_list":null,"apc_paid":null,"fwci":6.1156,"has_fulltext":true,"cited_by_count":51,"citation_normalized_percentile":{"value":0.96566639,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"59","issue":"7","first_page":"5938","last_page":"5952"},"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":0.9926000237464905,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9922000169754028,"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/flops","display_name":"FLOPS","score":0.8248127698898315},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7875415086746216},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.7219264507293701},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7036860585212708},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.5925554037094116},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5843476057052612},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5415563583374023},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5400742888450623},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.5267759561538696},{"id":"https://openalex.org/keywords/pointwise","display_name":"Pointwise","score":0.4903533458709717},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.47737976908683777},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.47482404112815857},{"id":"https://openalex.org/keywords/computational-complexity-theory","display_name":"Computational complexity theory","score":0.45415085554122925},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4538820683956146},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4146113395690918},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3235132694244385},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.31264275312423706},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.236727774143219},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.13098379969596863}],"concepts":[{"id":"https://openalex.org/C3826847","wikidata":"https://www.wikidata.org/wiki/Q188768","display_name":"FLOPS","level":2,"score":0.8248127698898315},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7875415086746216},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.7219264507293701},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7036860585212708},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.5925554037094116},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5843476057052612},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5415563583374023},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5400742888450623},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.5267759561538696},{"id":"https://openalex.org/C2777984123","wikidata":"https://www.wikidata.org/wiki/Q9248237","display_name":"Pointwise","level":2,"score":0.4903533458709717},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.47737976908683777},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.47482404112815857},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.45415085554122925},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4538820683956146},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4146113395690918},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3235132694244385},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.31264275312423706},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.236727774143219},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13098379969596863},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","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},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"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/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tgrs.2020.3024730","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2020.3024730","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:zenodo.org:8071073","is_oa":true,"landing_page_url":"https://zenodo.org/record/8071073","pdf_url":"https://zenodo.org/record/8071073","source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"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":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"pmh:oai:zenodo.org:8071073","is_oa":true,"landing_page_url":"https://zenodo.org/record/8071073","pdf_url":"https://zenodo.org/record/8071073","source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"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":"info:eu-repo/semantics/article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4648944835","display_name":null,"funder_award_id":"734541 (EOXPOSURE)","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"}],"funders":[{"id":"https://openalex.org/F4320320300","display_name":"European Commission","ror":"https://ror.org/00k4n6c32"},{"id":"https://openalex.org/F4320321764","display_name":"Ministerio de Educaci\u00f3n, Cultura y Deporte","ror":"https://ror.org/03nc27g21"},{"id":"https://openalex.org/F4320328352","display_name":"Junta de Extremadura","ror":"https://ror.org/01df4mv68"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3089820912.pdf","grobid_xml":"https://content.openalex.org/works/W3089820912.grobid-xml"},"referenced_works_count":90,"referenced_works":["https://openalex.org/W1531110464","https://openalex.org/W1663973292","https://openalex.org/W1665214252","https://openalex.org/W1836465849","https://openalex.org/W1840106123","https://openalex.org/W1932847118","https://openalex.org/W1969733464","https://openalex.org/W2001068000","https://openalex.org/W2001298023","https://openalex.org/W2006175358","https://openalex.org/W2010265430","https://openalex.org/W2010797000","https://openalex.org/W2012273471","https://openalex.org/W2067532478","https://openalex.org/W2081562328","https://openalex.org/W2085625911","https://openalex.org/W2087263574","https://openalex.org/W2092071303","https://openalex.org/W2095687521","https://openalex.org/W2098057602","https://openalex.org/W2101711129","https://openalex.org/W2103734061","https://openalex.org/W2118020653","https://openalex.org/W2121494034","https://openalex.org/W2136251662","https://openalex.org/W2136656942","https://openalex.org/W2159607295","https://openalex.org/W2161742217","https://openalex.org/W2167583754","https://openalex.org/W2170240176","https://openalex.org/W2218047931","https://openalex.org/W2417303407","https://openalex.org/W2519653196","https://openalex.org/W2531409750","https://openalex.org/W2538244214","https://openalex.org/W2548776929","https://openalex.org/W2549139847","https://openalex.org/W2550848904","https://openalex.org/W2593380010","https://openalex.org/W2594639291","https://openalex.org/W2612445135","https://openalex.org/W2614256707","https://openalex.org/W2761383769","https://openalex.org/W2764034829","https://openalex.org/W2764276316","https://openalex.org/W2767805377","https://openalex.org/W2772452219","https://openalex.org/W2782522152","https://openalex.org/W2792827505","https://openalex.org/W2793927960","https://openalex.org/W2794284562","https://openalex.org/W2809113079","https://openalex.org/W2888119354","https://openalex.org/W2890246415","https://openalex.org/W2892075618","https://openalex.org/W2896847173","https://openalex.org/W2898381489","https://openalex.org/W2914331134","https://openalex.org/W2919115771","https://openalex.org/W2941141441","https://openalex.org/W2949117887","https://openalex.org/W2963012544","https://openalex.org/W2963589041","https://openalex.org/W2963844898","https://openalex.org/W2963982496","https://openalex.org/W2976477742","https://openalex.org/W2977002487","https://openalex.org/W2979730033","https://openalex.org/W2979785627","https://openalex.org/W2982619380","https://openalex.org/W2983255812","https://openalex.org/W2991182394","https://openalex.org/W2991616716","https://openalex.org/W3003552243","https://openalex.org/W3015571647","https://openalex.org/W3102127038","https://openalex.org/W3103753223","https://openalex.org/W4297775537","https://openalex.org/W4301109526","https://openalex.org/W6637242042","https://openalex.org/W6638667902","https://openalex.org/W6685053522","https://openalex.org/W6718212895","https://openalex.org/W6728184133","https://openalex.org/W6734185594","https://openalex.org/W6737664043","https://openalex.org/W6752548847","https://openalex.org/W6754322854","https://openalex.org/W6768730371","https://openalex.org/W6770560719"],"related_works":["https://openalex.org/W4362597605","https://openalex.org/W1574414179","https://openalex.org/W4297676672","https://openalex.org/W3009056573","https://openalex.org/W2922073769","https://openalex.org/W4281702477","https://openalex.org/W2490526372","https://openalex.org/W4376166922","https://openalex.org/W4378510483","https://openalex.org/W3128011703"],"abstract_inverted_index":{"Convolutional":[0],"neural":[1],"networks":[2],"(CNNs)":[3],"have":[4],"proven":[5],"to":[6,23,28,58,66,76,98,191],"be":[7,55],"a":[8,47,68,121,157],"powerful":[9],"tool":[10],"for":[11,129],"the":[12,31,35,64,86,99,102,108,111,115,136,141,145,162,179],"classification":[13,131,194,213],"of":[14,46,50,71,88,101,110,138,144,149,209],"hyperspectral":[15],"images":[16],"(HSIs).":[17],"The":[18,153,183],"CNN":[19,124,187],"kernels":[20,43,89],"are":[21,44,82],"able":[22],"naturally":[24],"include":[25],"spatial":[26],"information":[27],"smooth":[29],"out":[30],"spectral":[32],"variability":[33],"and":[34,140,199,212],"noise":[36],"present":[37],"in":[38,147,165,207],"HSI":[39,130,193],"data.":[40],"However,":[41],"these":[42],"composed":[45],"large":[48,69],"number":[49,137],"learning":[51],"parameters":[52,139,171],"that":[53,132,177],"must":[54],"correctly":[56],"adjusted":[57],"achieve":[59],"good":[60],"performance.":[61],"This":[62,105],"forces":[63],"model":[65,146],"consume":[67],"amount":[70],"training":[72],"data,":[73],"being":[74],"prone":[75],"overfitting":[77],"when":[78],"limited":[79],"labeled":[80],"samples":[81],"available.":[83],"In":[84],"addition,":[85],"execution":[87],"is":[90],"computationally":[91],"very":[92,204],"expensive,":[93],"increasing":[94],"quadratically":[95],"with":[96,174],"respect":[97],"size":[100],"convolution":[103],"filter.":[104],"significantly":[106],"reduces":[107,134],"performance":[109,211],"model.":[112],"To":[113],"overcome":[114],"aforementioned":[116],"limitations,":[117],"this":[118],"work":[119],"presents":[120],"new":[122],"few-parameter":[123],"(based":[125],"on":[126],"shift":[127,158],"operations)":[128],"dramatically":[133],"both":[135],"computational":[142,210],"complexity":[143],"terms":[148,208],"floating-point":[150],"operations":[151],"(FLOPs).":[152],"operational":[154],"module":[155],"combines":[156],"kernel":[159],"(which":[160],"adjusts":[161],"input":[163],"data":[164,201],"particular":[166],"directions":[167],"without":[168],"involving":[169],"any":[170],"nor":[172],"FLOPs)":[173],"pointwise":[175],"convolutions":[176],"perform":[178],"feature":[180],"extraction":[181],"stage.":[182],"newly":[184],"developed":[185],"shift-based":[186],"has":[188],"been":[189],"employed":[190],"conduct":[192],"over":[195],"five":[196],"widely":[197],"used":[198],"challenging":[200],"sets,":[202],"achieving":[203],"promising":[205],"results":[206],"accuracy.":[214]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":12},{"year":2022,"cited_by_count":11},{"year":2021,"cited_by_count":9}],"updated_date":"2026-04-06T07:47:59.780226","created_date":"2025-10-10T00:00:00"}
