{"id":"https://openalex.org/W4401416201","doi":"https://doi.org/10.1109/cec60901.2024.10612014","title":"An Evolutionary Compact Deep Transfer Learning with CNN for Hyper-Parameter Tuning in Temporal Sorting of Plant Growth","display_name":"An Evolutionary Compact Deep Transfer Learning with CNN for Hyper-Parameter Tuning in Temporal Sorting of Plant Growth","publication_year":2024,"publication_date":"2024-06-30","ids":{"openalex":"https://openalex.org/W4401416201","doi":"https://doi.org/10.1109/cec60901.2024.10612014"},"language":"en","primary_location":{"id":"doi:10.1109/cec60901.2024.10612014","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cec60901.2024.10612014","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE Congress on Evolutionary Computation (CEC)","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/A5019996443","display_name":"Seyed Jalaleddin Mousavirad","orcid":"https://orcid.org/0000-0001-8661-7578"},"institutions":[{"id":"https://openalex.org/I56475706","display_name":"Mid Sweden University","ror":"https://ror.org/019k1pd13","country_code":"SE","type":"education","lineage":["https://openalex.org/I56475706"]}],"countries":["SE"],"is_corresponding":true,"raw_author_name":"Seyed Jalaleddin Mousavirad","raw_affiliation_strings":["Mid Sweden University,Department of Computer and Electrical Engineering,Sundsvall,Sweden"],"affiliations":[{"raw_affiliation_string":"Mid Sweden University,Department of Computer and Electrical Engineering,Sundsvall,Sweden","institution_ids":["https://openalex.org/I56475706"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009880754","display_name":"Irida Shallari","orcid":"https://orcid.org/0000-0002-3774-4850"},"institutions":[{"id":"https://openalex.org/I56475706","display_name":"Mid Sweden University","ror":"https://ror.org/019k1pd13","country_code":"SE","type":"education","lineage":["https://openalex.org/I56475706"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Irida Shallari","raw_affiliation_strings":["Mid Sweden University,Department of Computer and Electrical Engineering,Sundsvall,Sweden"],"affiliations":[{"raw_affiliation_string":"Mid Sweden University,Department of Computer and Electrical Engineering,Sundsvall,Sweden","institution_ids":["https://openalex.org/I56475706"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036351446","display_name":"Mattias O\u2019Nils","orcid":"https://orcid.org/0000-0001-8607-4083"},"institutions":[{"id":"https://openalex.org/I56475706","display_name":"Mid Sweden University","ror":"https://ror.org/019k1pd13","country_code":"SE","type":"education","lineage":["https://openalex.org/I56475706"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Mattias O'Nils","raw_affiliation_strings":["Mid Sweden University,Department of Computer and Electrical Engineering,Sundsvall,Sweden"],"affiliations":[{"raw_affiliation_string":"Mid Sweden University,Department of Computer and Electrical Engineering,Sundsvall,Sweden","institution_ids":["https://openalex.org/I56475706"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5019996443"],"corresponding_institution_ids":["https://openalex.org/I56475706"],"apc_list":null,"apc_paid":null,"fwci":3.2418,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.91511414,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9983999729156494,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9983999729156494,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T14365","display_name":"Leaf Properties and Growth Measurement","score":0.9930999875068665,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T12093","display_name":"Greenhouse Technology and Climate Control","score":0.9801999926567078,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/sorting","display_name":"Sorting","score":0.7281251549720764},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.653835654258728},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.614902913570404},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5910984873771667},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5206626653671265},{"id":"https://openalex.org/keywords/biological-system","display_name":"Biological system","score":0.34735527634620667},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3284270167350769},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.18798702955245972},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.1447146236896515}],"concepts":[{"id":"https://openalex.org/C111696304","wikidata":"https://www.wikidata.org/wiki/Q2303697","display_name":"Sorting","level":2,"score":0.7281251549720764},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.653835654258728},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.614902913570404},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5910984873771667},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5206626653671265},{"id":"https://openalex.org/C186060115","wikidata":"https://www.wikidata.org/wiki/Q30336093","display_name":"Biological system","level":1,"score":0.34735527634620667},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3284270167350769},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.18798702955245972},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.1447146236896515}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cec60901.2024.10612014","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cec60901.2024.10612014","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE Congress on Evolutionary Computation (CEC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Zero hunger","id":"https://metadata.un.org/sdg/2","score":0.800000011920929}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1595159159","https://openalex.org/W2042253843","https://openalex.org/W2084325791","https://openalex.org/W2108598243","https://openalex.org/W2112036188","https://openalex.org/W2131613989","https://openalex.org/W2148211213","https://openalex.org/W2151554678","https://openalex.org/W2157494358","https://openalex.org/W2165299997","https://openalex.org/W2549139847","https://openalex.org/W2946326863","https://openalex.org/W2963125010","https://openalex.org/W2963163009","https://openalex.org/W2970117169","https://openalex.org/W3026381557","https://openalex.org/W3047930143","https://openalex.org/W3151277442","https://openalex.org/W4246193833","https://openalex.org/W4294811716","https://openalex.org/W4310748454","https://openalex.org/W4312270425","https://openalex.org/W4312814697","https://openalex.org/W4321609025","https://openalex.org/W4379260314","https://openalex.org/W4392978828"],"related_works":["https://openalex.org/W4206357785","https://openalex.org/W4281381188","https://openalex.org/W3192840557","https://openalex.org/W2951211570","https://openalex.org/W4375928479","https://openalex.org/W3167935049","https://openalex.org/W3023427754","https://openalex.org/W3131673289","https://openalex.org/W4393011546","https://openalex.org/W3198847674"],"abstract_inverted_index":{"The":[0,32,82,225],"efficient":[1],"management":[2],"of":[3,10,28,72,89,103,152,204,233],"agricultural":[4],"resources":[5],"requires":[6],"a":[7,45,64,87,94,97,212],"deep":[8,76,117],"understanding":[9],"plant":[11,37,104,199],"growth":[12,38,200],"dynamics.":[13],"This":[14],"research":[15],"focuses":[16],"on":[17,129],"Sweden's":[18],"forestry":[19],"sector":[20],"and":[21,75,182],"explicitly":[22],"addresses":[23],"the":[24,70],"crucial":[25],"early":[26],"stages":[27],"pine":[29],"tree":[30],"development.":[31],"main":[33],"difficulty":[34],"in":[35,142,222],"categorising":[36],"over":[39,100],"time":[40],"is":[41,150,208],"that":[42,68,91,147,209],"instances":[43,52],"within":[44],"given":[46],"category":[47],"are":[48],"not":[49],"identical,":[50],"while":[51],"from":[53],"different":[54],"categories":[55],"may":[56],"have":[57],"similarities.":[58],"In":[59],"this":[60],"context,":[61],"we":[62,157,192],"present":[63],"novel":[65],"measurement":[66],"system":[67,85],"integrates":[69],"capa-bilities":[71],"evolutionary":[73,155],"computation":[74,214],"transfer":[77,118],"learning":[78,119],"using":[79],"image":[80,83],"data.":[81],"acquisition":[84],"includes":[86],"tray":[88],"plates":[90],"moves":[92],"through":[93],"nursery,":[95],"generating":[96],"dataset":[98],"captured":[99],"44":[101],"days":[102],"growth.":[105],"Our":[106],"newly":[107],"proposed":[108,193,206,226],"algorithm,":[109,156],"EvoSqueezeNet,":[110],"employs":[111],"various":[112],"search":[113,161,217],"strategies":[114],"for":[115,126,197,216],"SqueezeNet":[116,127],"to":[120,138,242],"find":[121],"proper":[122],"hyper-parameters.":[123],"We":[124],"opted":[125],"based":[128],"our":[130,143,148,205],"preliminary":[131],"studies,":[132],"revealing":[133],"its":[134,220,238],"superior":[135,239],"performance":[136,240],"compared":[137,241],"other":[139],"pre-trained":[140],"models":[141],"case":[144],"study.":[145],"Given":[146],"approach":[149],"independent":[151],"any":[153],"specific":[154],"utilised":[158],"five":[159,194],"distinct":[160],"strategies.":[162],"These":[163],"include":[164],"Differential":[165],"Evolution":[166,175],"(DE),":[167],"Particle":[168],"Swarm":[169],"Optimisation":[170],"(PSO),":[171],"Covariance":[172],"Ma-trix":[173],"Adaptation":[174,188],"Strategy":[176],"(CMA-ES),":[177],"Comprehensive":[178],"Learning":[179],"PSO":[180],"(CLPSO),":[181],"Linear":[183],"Population":[184],"Size":[185],"Reduction":[186],"Success-History":[187],"DE":[189],"(LSHADE).":[190],"Consequently,":[191],"EvoSqueezeNet":[195,227],"schemes":[196],"temporal":[198],"categorisation.":[201],"One":[202],"characteristic":[203],"model":[207],"it":[210],"uses":[211],"limited":[213],"budget":[215],"strategies,":[218],"en-hancing":[219],"applicability":[221],"real-world":[223],"applications.":[224],"methodology":[228],"demonstrates":[229],"an":[230],"error":[231],"reduction":[232],"more":[234],"than":[235],"40%,":[236],"showcasing":[237],"competing":[243],"methods.":[244]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":1}],"updated_date":"2025-12-26T23:08:49.675405","created_date":"2025-10-10T00:00:00"}