{"id":"https://openalex.org/W2933980179","doi":"https://doi.org/10.1109/access.2019.2906369","title":"Automatic Convolutional Neural Architecture Search for Image Classification Under Different Scenes","display_name":"Automatic Convolutional Neural Architecture Search for Image Classification Under Different Scenes","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2933980179","doi":"https://doi.org/10.1109/access.2019.2906369","mag":"2933980179"},"language":"en","primary_location":{"id":"doi:10.1109/access.2019.2906369","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2906369","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08676019.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/ielx7/6287639/8600701/08676019.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5024296105","display_name":"Yu Weng","orcid":"https://orcid.org/0000-0002-0787-550X"},"institutions":[{"id":"https://openalex.org/I145897649","display_name":"Minzu University of China","ror":"https://ror.org/0044e2g62","country_code":"CN","type":"education","lineage":["https://openalex.org/I145897649"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yu Weng","raw_affiliation_strings":["College of Information Engineering, Minzu University of China, Beijing, China"],"affiliations":[{"raw_affiliation_string":"College of Information Engineering, Minzu University of China, Beijing, China","institution_ids":["https://openalex.org/I145897649"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032994203","display_name":"Tianbao Zhou","orcid":"https://orcid.org/0000-0002-2133-059X"},"institutions":[{"id":"https://openalex.org/I145897649","display_name":"Minzu University of China","ror":"https://ror.org/0044e2g62","country_code":"CN","type":"education","lineage":["https://openalex.org/I145897649"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianbao Zhou","raw_affiliation_strings":["College of Information Engineering, Minzu University of China, Beijing, China"],"affiliations":[{"raw_affiliation_string":"College of Information Engineering, Minzu University of China, Beijing, China","institution_ids":["https://openalex.org/I145897649"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100349464","display_name":"Lei Liu","orcid":"https://orcid.org/0000-0001-5063-2864"},"institutions":[{"id":"https://openalex.org/I145897649","display_name":"Minzu University of China","ror":"https://ror.org/0044e2g62","country_code":"CN","type":"education","lineage":["https://openalex.org/I145897649"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Liu","raw_affiliation_strings":["College of Information Engineering, Minzu University of China, Beijing, China"],"affiliations":[{"raw_affiliation_string":"College of Information Engineering, Minzu University of China, Beijing, China","institution_ids":["https://openalex.org/I145897649"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001899204","display_name":"Chunlei Xia","orcid":"https://orcid.org/0000-0002-6379-9863"},"institutions":[{"id":"https://openalex.org/I145897649","display_name":"Minzu University of China","ror":"https://ror.org/0044e2g62","country_code":"CN","type":"education","lineage":["https://openalex.org/I145897649"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chunlei Xia","raw_affiliation_strings":["College of Information Engineering, Minzu University of China, Beijing, China"],"affiliations":[{"raw_affiliation_string":"College of Information Engineering, Minzu University of China, Beijing, China","institution_ids":["https://openalex.org/I145897649"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5024296105"],"corresponding_institution_ids":["https://openalex.org/I145897649"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":3.9845,"has_fulltext":true,"cited_by_count":53,"citation_normalized_percentile":{"value":0.95022068,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":"7","issue":null,"first_page":"38495","last_page":"38506"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":1.0,"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/T10036","display_name":"Advanced Neural Network Applications","score":1.0,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9972000122070312,"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/T11992","display_name":"CCD and CMOS Imaging Sensors","score":0.9965999722480774,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"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/computer-science","display_name":"Computer science","score":0.8530005216598511},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7552273273468018},{"id":"https://openalex.org/keywords/mnist-database","display_name":"MNIST database","score":0.6938733458518982},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.6873902678489685},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6232913136482239},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.6224196553230286},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4864963889122009},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4665956497192383},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4052852988243103},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.39454102516174316},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.3774617910385132}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8530005216598511},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7552273273468018},{"id":"https://openalex.org/C190502265","wikidata":"https://www.wikidata.org/wiki/Q17069496","display_name":"MNIST database","level":3,"score":0.6938733458518982},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.6873902678489685},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6232913136482239},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.6224196553230286},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4864963889122009},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4665956497192383},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4052852988243103},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.39454102516174316},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3774617910385132},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2019.2906369","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2906369","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08676019.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:5c6feae8f81b4130a51d72ba129c7be2","is_oa":true,"landing_page_url":"https://doaj.org/article/5c6feae8f81b4130a51d72ba129c7be2","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"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 7, Pp 38495-38506 (2019)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2019.2906369","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2906369","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08676019.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":[{"id":"https://openalex.org/G1121271761","display_name":null,"funder_award_id":"Program","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1231421488","display_name":null,"funder_award_id":"under","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3141632398","display_name":null,"funder_award_id":"61772575","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G391238517","display_name":null,"funder_award_id":", and","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4465251987","display_name":null,"funder_award_id":"2017YFB1402101","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5347105962","display_name":null,"funder_award_id":"B14021","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5994120800","display_name":null,"funder_award_id":"Natural","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8365407071","display_name":null,"funder_award_id":"1402101","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2933980179.pdf","grobid_xml":"https://content.openalex.org/works/W2933980179.grobid-xml"},"referenced_works_count":66,"referenced_works":["https://openalex.org/W1512748932","https://openalex.org/W1581066146","https://openalex.org/W1686810756","https://openalex.org/W1966124573","https://openalex.org/W2045491133","https://openalex.org/W2097117768","https://openalex.org/W2111935653","https://openalex.org/W2119814172","https://openalex.org/W2163605009","https://openalex.org/W2171658832","https://openalex.org/W2194775991","https://openalex.org/W2329582438","https://openalex.org/W2408279554","https://openalex.org/W2531409750","https://openalex.org/W2553303224","https://openalex.org/W2593744649","https://openalex.org/W2606006859","https://openalex.org/W2610817424","https://openalex.org/W2618398196","https://openalex.org/W2626124486","https://openalex.org/W2737551799","https://openalex.org/W2751836095","https://openalex.org/W2752782242","https://openalex.org/W2753661786","https://openalex.org/W2769653148","https://openalex.org/W2771751675","https://openalex.org/W2773706593","https://openalex.org/W2783430431","https://openalex.org/W2788853733","https://openalex.org/W2793947836","https://openalex.org/W2796265726","https://openalex.org/W2804252870","https://openalex.org/W2809899846","https://openalex.org/W2888429796","https://openalex.org/W2893541821","https://openalex.org/W2897510551","https://openalex.org/W2902994895","https://openalex.org/W2907134525","https://openalex.org/W2951104886","https://openalex.org/W2963125010","https://openalex.org/W2963446712","https://openalex.org/W2963778169","https://openalex.org/W2963821229","https://openalex.org/W2964081807","https://openalex.org/W4255158661","https://openalex.org/W4295185264","https://openalex.org/W4300687381","https://openalex.org/W6634833660","https://openalex.org/W6637373629","https://openalex.org/W6661524384","https://openalex.org/W6684191040","https://openalex.org/W6714181750","https://openalex.org/W6729956949","https://openalex.org/W6729972426","https://openalex.org/W6734864916","https://openalex.org/W6738373677","https://openalex.org/W6743745977","https://openalex.org/W6745614327","https://openalex.org/W6745748327","https://openalex.org/W6746693648","https://openalex.org/W6748057086","https://openalex.org/W6748587240","https://openalex.org/W6752515464","https://openalex.org/W6753701838","https://openalex.org/W6756610502","https://openalex.org/W6758201965"],"related_works":["https://openalex.org/W3036048022","https://openalex.org/W4309224979","https://openalex.org/W3026879719","https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W3167935049","https://openalex.org/W3029198973","https://openalex.org/W2952813363"],"abstract_inverted_index":{"The":[0,67,185],"recent":[1],"advances":[2],"in":[3,114,181],"convolutional":[4,62],"neural":[5,63],"networks":[6],"(CNNs)":[7],"have":[8,95],"used":[9],"for":[10,82,98,125,222,232],"image":[11,20,57],"classification":[12,58],"to":[13,27,54,107],"achieve":[14,28,163],"remarkable":[15],"results.":[16],"Different":[17],"fields":[18],"of":[19,110,147,187,196,212],"datasets":[21],"will":[22],"need":[23],"different":[24,56,145],"CNN":[25,35,128],"architectures":[26],"exceptional":[29],"performance.":[30],"However,":[31],"designing":[32],"a":[33,38,61,83,120,164,219,229],"good":[34],"architecture":[36,64,81,139,197,213,221,231],"is":[37,69,133],"computationally":[39],"expensive":[40],"task":[41],"and":[42,90,150,159,173,209],"requires":[43],"expert":[44],"knowledge.":[45],"In":[46],"this":[47],"paper,":[48],"we":[49],"propose":[50,119],"an":[51],"effective":[52],"framework":[53,68,216],"solve":[55],"tasks":[59],"using":[60],"search":[65,93,116,123,131,140],"(CNAS).":[66],"inspired":[70],"by":[71,155,202],"current":[72],"research":[73],"on":[74,135,169],"NAS,":[75],"which":[76],"automatically":[77],"learns":[78],"the":[79,108,115,127,171,178,183,188,194,207,210,215],"best":[80],"specific":[84],"training":[85],"dataset,":[86],"such":[87,225,235],"as":[88,226,236],"MNIST":[89],"CIFAR-10.":[91],"Many":[92],"algorithms":[94],"been":[96,105,200],"proposed":[97],"implementing":[99],"NAS;":[100],"however,":[101],"insufficient":[102],"attention":[103],"has":[104,190,199],"paid":[106],"selection":[109],"primitive":[111],"operations":[112],"(POs)":[113],"space.":[117],"We":[118,162,176],"more":[121],"efficient":[122],"space":[124],"learning":[126],"architecture.":[129,184],"Our":[130],"algorithm":[132],"based":[134],"Darts":[136,168],"(a":[137],"differential":[138],"method),":[141],"but":[142,193,228],"it":[143],"considers":[144],"numbers":[146],"intermediate":[148],"nodes":[149],"replaces":[151],"some":[152],"unused":[153],"POs":[154],"channel":[156],"shuffle":[157],"operation":[158,180],"squeeze-and-excitation":[160],"operation.":[161],"better":[165],"performance":[166,186,208],"than":[167],"both":[170],"CIFAR10/CIFA100":[172],"Tiny-ImageNet":[174],"datasets.":[175],"retain":[177],"none":[179],"deriving":[182],"model":[189],"slightly":[191],"decreased,":[192],"number":[195,211],"parameters":[198],"reduced":[201],"approximately":[203],"40%.":[204],"To":[205],"balance":[206],"parameters,":[214],"can":[217],"learn":[218],"dense":[220],"high-performance":[223],"machines,":[224],"servers,":[227],"sparse":[230],"resource-constrained":[233],"devices,":[234],"embedded":[237],"systems":[238],"or":[239],"mobile":[240],"devices.":[241]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":14},{"year":2020,"cited_by_count":10},{"year":2019,"cited_by_count":10}],"updated_date":"2026-04-13T07:58:08.660418","created_date":"2025-10-10T00:00:00"}
