{"id":"https://openalex.org/W2993515356","doi":"https://doi.org/10.1109/access.2019.2955560","title":"Shelf Commodity Identification Method Based on Hybrid Fully Convolutional Automatic Encoder","display_name":"Shelf Commodity Identification Method Based on Hybrid Fully Convolutional Automatic Encoder","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2993515356","doi":"https://doi.org/10.1109/access.2019.2955560","mag":"2993515356"},"language":"en","primary_location":{"id":"doi:10.1109/access.2019.2955560","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2955560","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08911324.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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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/ielx7/6287639/8600701/08911324.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5056032545","display_name":"Aofeng Cheng","orcid":"https://orcid.org/0000-0003-0573-636X"},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Aofeng Cheng","raw_affiliation_strings":["School of Mechanical and Electric Engineering, Jiangsu Provincial Key Laboratory of Advanced Robotics, Soochow University, Suzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-0573-636X","affiliations":[{"raw_affiliation_string":"School of Mechanical and Electric Engineering, Jiangsu Provincial Key Laboratory of Advanced Robotics, Soochow University, Suzhou, China","institution_ids":["https://openalex.org/I3923682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067992824","display_name":"Guodong Chen","orcid":"https://orcid.org/0000-0002-4835-708X"},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guodong Chen","raw_affiliation_strings":["School of Mechanical and Electric Engineering, Jiangsu Provincial Key Laboratory of Advanced Robotics, Soochow University, Suzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-4835-708X","affiliations":[{"raw_affiliation_string":"School of Mechanical and Electric Engineering, Jiangsu Provincial Key Laboratory of Advanced Robotics, Soochow University, Suzhou, China","institution_ids":["https://openalex.org/I3923682"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100401052","display_name":"Zheng Wang","orcid":"https://orcid.org/0000-0001-6787-5985"},"institutions":[{"id":"https://openalex.org/I4210144482","display_name":"Shanghai Sixth People's Hospital","ror":"https://ror.org/049zrh188","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210144482"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zheng Wang","raw_affiliation_strings":["Shanghai Jiaotong University Affiliated Sixth People\u2019s Hospital, Shanghai Jiaotong University, Shanghai, China","Shanghai Jiaotong University Affiliated Sixth People's Hospital, Shanghai Jiaotong University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0001-6787-5985","affiliations":[{"raw_affiliation_string":"Shanghai Jiaotong University Affiliated Sixth People\u2019s Hospital, Shanghai Jiaotong University, Shanghai, China","institution_ids":["https://openalex.org/I4210144482"]},{"raw_affiliation_string":"Shanghai Jiaotong University Affiliated Sixth People's Hospital, Shanghai Jiaotong University, Shanghai, China","institution_ids":["https://openalex.org/I4210144482"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5056032545"],"corresponding_institution_ids":["https://openalex.org/I3923682"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.2208,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.64732447,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"7","issue":null,"first_page":"169899","last_page":"169907"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9854999780654907,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9854999780654907,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"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/T14319","display_name":"Currency Recognition and Detection","score":0.9740999937057495,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9609000086784363,"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/autoencoder","display_name":"Autoencoder","score":0.9123015403747559},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7961214780807495},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7400035858154297},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7166630625724792},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6323304772377014},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6122274994850159},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5650252103805542},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.46484723687171936},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.4458063840866089},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.4442857503890991},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4318523406982422},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.4164383113384247},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.41451042890548706},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3537292182445526}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.9123015403747559},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7961214780807495},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7400035858154297},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7166630625724792},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6323304772377014},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6122274994850159},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5650252103805542},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.46484723687171936},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.4458063840866089},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.4442857503890991},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4318523406982422},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.4164383113384247},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.41451042890548706},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3537292182445526},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2019.2955560","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2955560","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08911324.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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:430ef5e3edfc4c1d8c85e459deb5fba4","is_oa":true,"landing_page_url":"https://doaj.org/article/430ef5e3edfc4c1d8c85e459deb5fba4","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 169899-169907 (2019)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2019.2955560","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2955560","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08911324.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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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/G6020590726","display_name":null,"funder_award_id":"U1509202","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"},{"id":"https://openalex.org/F4320321605","display_name":"Government of Jiangsu Province","ror":"https://ror.org/004svx814"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2993515356.pdf","grobid_xml":"https://content.openalex.org/works/W2993515356.grobid-xml"},"referenced_works_count":35,"referenced_works":["https://openalex.org/W2176583664","https://openalex.org/W2337890890","https://openalex.org/W2395611524","https://openalex.org/W2522541378","https://openalex.org/W2527938858","https://openalex.org/W2560023338","https://openalex.org/W2569100269","https://openalex.org/W2593617942","https://openalex.org/W2616727008","https://openalex.org/W2630837129","https://openalex.org/W2737373222","https://openalex.org/W2742398205","https://openalex.org/W2760340275","https://openalex.org/W2762439315","https://openalex.org/W2781137302","https://openalex.org/W2791719807","https://openalex.org/W2792767783","https://openalex.org/W2800306924","https://openalex.org/W2814568980","https://openalex.org/W2887036838","https://openalex.org/W2892096486","https://openalex.org/W2896971046","https://openalex.org/W2905380950","https://openalex.org/W2907547290","https://openalex.org/W2914234035","https://openalex.org/W2963226018","https://openalex.org/W2963230283","https://openalex.org/W2963659230","https://openalex.org/W2963739249","https://openalex.org/W2966975099","https://openalex.org/W3099112683","https://openalex.org/W3104766717","https://openalex.org/W6703477647","https://openalex.org/W6739696289","https://openalex.org/W6749375246"],"related_works":["https://openalex.org/W3013693939","https://openalex.org/W2566616303","https://openalex.org/W2159052453","https://openalex.org/W3131327266","https://openalex.org/W2734887215","https://openalex.org/W2803255133","https://openalex.org/W4297051394","https://openalex.org/W2752972570","https://openalex.org/W4386815338","https://openalex.org/W2145836866"],"abstract_inverted_index":{"At":[0],"present,":[1],"the":[2,25,62,66,72,78,82,87,90,96,102,110,121,135,150],"semantic":[3],"information":[4],"segmentation":[5],"algorithms":[6,33],"mainly":[7],"include":[8],"FCN":[9,63],"(Fully":[10],"Convolutional":[11],"Network),":[12,17],"PSPNet":[13],"(Pyramid":[14],"Scene":[15],"Parsing":[16],"Deeplab":[18],"and":[19,52,75,101,138],"so":[20,108],"on.":[21],"In":[22],"view":[23],"of":[24,28,71,141,152],"inadequate":[26],"results":[27,112,118],"features":[29,92],"extracted":[30],"by":[31,95,144,156],"these":[32],"from":[34],"RGB":[35],"image,":[36],"a":[37],"hybrid":[38,122],"fully":[39,48,123],"convolutional":[40,49,124],"autoencoder":[41,99,125],"neural":[42,50,142],"network":[43,51,143],"(HFCAN)":[44],"structure,":[45],"which":[46],"introduces":[47],"stacked":[53,97],"sparse":[54,98],"autoencoder,":[55],"is":[56],"proposed":[57,127],"in":[58,128],"this":[59,129],"paper.":[60],"Using":[61],"to":[64],"generate":[65],"thermal":[67],"high-dimensional":[68],"feature":[69,84],"map":[70],"shelf":[73,153],"commodity,":[74],"then":[76],"performing":[77],"up-sampling":[79,88],"operation":[80],"on":[81],"segmented":[83],"map.":[85],"During":[86],"operation,":[89],"convolution":[91],"are":[93,106,113],"refined":[94],"(SAE),":[100],"image":[103],"boundary":[104],"details":[105],"retained,":[107],"that":[109,120],"classification":[111],"more":[114],"accurate.":[115],"The":[116],"experimental":[117],"show":[119],"model":[126],"paper":[130],"can":[131],"not":[132],"only":[133],"shorten":[134],"training":[136],"time":[137,140],"testing":[139],"nearly":[145,157],"50%,":[146],"but":[147],"also":[148],"improve":[149],"accuracy":[151],"commodity":[154],"identification":[155],"95%.":[158]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
