{"id":"https://openalex.org/W4308236032","doi":"https://doi.org/10.1109/icip46576.2022.9897868","title":"Deep Ensemble Learning Model Based on Covariance Pooling of Multi-Layer CNN Features","display_name":"Deep Ensemble Learning Model Based on Covariance Pooling of Multi-Layer CNN Features","publication_year":2022,"publication_date":"2022-10-16","ids":{"openalex":"https://openalex.org/W4308236032","doi":"https://doi.org/10.1109/icip46576.2022.9897868"},"language":"en","primary_location":{"id":"doi:10.1109/icip46576.2022.9897868","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip46576.2022.9897868","pdf_url":null,"source":{"id":"https://openalex.org/S4363607719","display_name":"2022 IEEE International Conference on Image Processing (ICIP)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://hal.science/hal-04263872","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5008569115","display_name":"Sara Akodad","orcid":"https://orcid.org/0000-0002-9553-4034"},"institutions":[{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"government","lineage":["https://openalex.org/I1294671590"]},{"id":"https://openalex.org/I15057530","display_name":"Universit\u00e9 de Bordeaux","ror":"https://ror.org/057qpr032","country_code":"FR","type":"education","lineage":["https://openalex.org/I15057530"]},{"id":"https://openalex.org/I4210157089","display_name":"Laboratoire de l'Int\u00e9gration du Mat\u00e9riau au Syst\u00e8me","ror":"https://ror.org/04nabhy78","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I1294671590","https://openalex.org/I15057530","https://openalex.org/I4210091158","https://openalex.org/I4210095849","https://openalex.org/I4210157089","https://openalex.org/I4210160189"]},{"id":"https://openalex.org/I4210160189","display_name":"Institut Polytechnique de Bordeaux","ror":"https://ror.org/054qv7y42","country_code":"FR","type":"education","lineage":["https://openalex.org/I4210160189"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Sara Akodad","raw_affiliation_strings":["Université de Bordeaux,CNRS, IMS, UMR 5218, Groupe Signal et Image,Talence,France,F-33405"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Université de Bordeaux,CNRS, IMS, UMR 5218, Groupe Signal et Image,Talence,France,F-33405","institution_ids":["https://openalex.org/I1294671590","https://openalex.org/I15057530","https://openalex.org/I4210157089","https://openalex.org/I4210160189"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037554238","display_name":"Lionel Bombrun","orcid":"https://orcid.org/0000-0001-9036-3988"},"institutions":[{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"government","lineage":["https://openalex.org/I1294671590"]},{"id":"https://openalex.org/I15057530","display_name":"Universit\u00e9 de Bordeaux","ror":"https://ror.org/057qpr032","country_code":"FR","type":"education","lineage":["https://openalex.org/I15057530"]},{"id":"https://openalex.org/I4210157089","display_name":"Laboratoire de l'Int\u00e9gration du Mat\u00e9riau au Syst\u00e8me","ror":"https://ror.org/04nabhy78","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I1294671590","https://openalex.org/I15057530","https://openalex.org/I4210091158","https://openalex.org/I4210095849","https://openalex.org/I4210157089","https://openalex.org/I4210160189"]},{"id":"https://openalex.org/I4210160189","display_name":"Institut Polytechnique de Bordeaux","ror":"https://ror.org/054qv7y42","country_code":"FR","type":"education","lineage":["https://openalex.org/I4210160189"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Lionel Bombrun","raw_affiliation_strings":["Université de Bordeaux,CNRS, IMS, UMR 5218, Groupe Signal et Image,Talence,France,F-33405"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Université de Bordeaux,CNRS, IMS, UMR 5218, Groupe Signal et Image,Talence,France,F-33405","institution_ids":["https://openalex.org/I1294671590","https://openalex.org/I15057530","https://openalex.org/I4210157089","https://openalex.org/I4210160189"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030416500","display_name":"Maria Pu\u0219ca\u0219u","orcid":null},"institutions":[{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"government","lineage":["https://openalex.org/I1294671590"]},{"id":"https://openalex.org/I15057530","display_name":"Universit\u00e9 de Bordeaux","ror":"https://ror.org/057qpr032","country_code":"FR","type":"education","lineage":["https://openalex.org/I15057530"]},{"id":"https://openalex.org/I4210157089","display_name":"Laboratoire de l'Int\u00e9gration du Mat\u00e9riau au Syst\u00e8me","ror":"https://ror.org/04nabhy78","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I1294671590","https://openalex.org/I15057530","https://openalex.org/I4210091158","https://openalex.org/I4210095849","https://openalex.org/I4210157089","https://openalex.org/I4210160189"]},{"id":"https://openalex.org/I4210160189","display_name":"Institut Polytechnique de Bordeaux","ror":"https://ror.org/054qv7y42","country_code":"FR","type":"education","lineage":["https://openalex.org/I4210160189"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Maria Puscasu","raw_affiliation_strings":["Université de Bordeaux,CNRS, IMS, UMR 5218, Groupe Signal et Image,Talence,France,F-33405"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Université de Bordeaux,CNRS, IMS, UMR 5218, Groupe Signal et Image,Talence,France,F-33405","institution_ids":["https://openalex.org/I1294671590","https://openalex.org/I15057530","https://openalex.org/I4210157089","https://openalex.org/I4210160189"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000395252","display_name":"Junshi Xia","orcid":"https://orcid.org/0000-0002-5586-6536"},"institutions":[{"id":"https://openalex.org/I4210126580","display_name":"RIKEN Center for Advanced Intelligence Project","ror":"https://ror.org/03ckxwf91","country_code":"JP","type":"facility","lineage":["https://openalex.org/I4210110652","https://openalex.org/I4210126580"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Junshi Xia","raw_affiliation_strings":["RIKEN Center for Advanced Intelligence Project (AIP),RIKEN,Tokyo,Japan,103-0027","RIKEN AIP - RIKEN Center for Advanced Intelligence Project [Tokyo] (Nihonbashi 1-chome Mitsui Building, 15th floor, \r\n1-4-1 Nihonbashi, \r\nChuo-ku, Tokyo \r\n103-0027, Japan - Japan)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"RIKEN Center for Advanced Intelligence Project (AIP),RIKEN,Tokyo,Japan,103-0027","institution_ids":["https://openalex.org/I4210126580"]},{"raw_affiliation_string":"RIKEN AIP - RIKEN Center for Advanced Intelligence Project [Tokyo] (Nihonbashi 1-chome Mitsui Building, 15th floor, \r\n1-4-1 Nihonbashi, \r\nChuo-ku, Tokyo \r\n103-0027, Japan - Japan)","institution_ids":["https://openalex.org/I4210126580"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084906943","display_name":"Christian Germain","orcid":"https://orcid.org/0000-0002-3097-8283"},"institutions":[{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"government","lineage":["https://openalex.org/I1294671590"]},{"id":"https://openalex.org/I15057530","display_name":"Universit\u00e9 de Bordeaux","ror":"https://ror.org/057qpr032","country_code":"FR","type":"education","lineage":["https://openalex.org/I15057530"]},{"id":"https://openalex.org/I4210157089","display_name":"Laboratoire de l'Int\u00e9gration du Mat\u00e9riau au Syst\u00e8me","ror":"https://ror.org/04nabhy78","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I1294671590","https://openalex.org/I15057530","https://openalex.org/I4210091158","https://openalex.org/I4210095849","https://openalex.org/I4210157089","https://openalex.org/I4210160189"]},{"id":"https://openalex.org/I4210160189","display_name":"Institut Polytechnique de Bordeaux","ror":"https://ror.org/054qv7y42","country_code":"FR","type":"education","lineage":["https://openalex.org/I4210160189"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Christian Germain","raw_affiliation_strings":["Université de Bordeaux,CNRS, IMS, UMR 5218, Groupe Signal et Image,Talence,France,F-33405"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Université de Bordeaux,CNRS, IMS, UMR 5218, Groupe Signal et Image,Talence,France,F-33405","institution_ids":["https://openalex.org/I1294671590","https://openalex.org/I15057530","https://openalex.org/I4210157089","https://openalex.org/I4210160189"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5042761955","display_name":"Yannick Berthoumieu","orcid":"https://orcid.org/0000-0002-7559-0602"},"institutions":[{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"government","lineage":["https://openalex.org/I1294671590"]},{"id":"https://openalex.org/I15057530","display_name":"Universit\u00e9 de Bordeaux","ror":"https://ror.org/057qpr032","country_code":"FR","type":"education","lineage":["https://openalex.org/I15057530"]},{"id":"https://openalex.org/I4210157089","display_name":"Laboratoire de l'Int\u00e9gration du Mat\u00e9riau au Syst\u00e8me","ror":"https://ror.org/04nabhy78","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I1294671590","https://openalex.org/I15057530","https://openalex.org/I4210091158","https://openalex.org/I4210095849","https://openalex.org/I4210157089","https://openalex.org/I4210160189"]},{"id":"https://openalex.org/I4210160189","display_name":"Institut Polytechnique de Bordeaux","ror":"https://ror.org/054qv7y42","country_code":"FR","type":"education","lineage":["https://openalex.org/I4210160189"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Yannick Berthoumieu","raw_affiliation_strings":["Université de Bordeaux,CNRS, IMS, UMR 5218, Groupe Signal et Image,Talence,France,F-33405"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Université de Bordeaux,CNRS, IMS, UMR 5218, Groupe Signal et Image,Talence,France,F-33405","institution_ids":["https://openalex.org/I1294671590","https://openalex.org/I15057530","https://openalex.org/I4210157089","https://openalex.org/I4210160189"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3562,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.53995157,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":94},"biblio":{"volume":"45","issue":null,"first_page":"1081","last_page":"1085"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9997000098228455,"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":0.9997000098228455,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9980999827384949,"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":0.9975000023841858,"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/pooling","display_name":"Pooling","score":0.8813759088516235},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7487142086029053},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7098225951194763},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6735371351242065},{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.6402689218521118},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6176090240478516},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5510460138320923},{"id":"https://openalex.org/keywords/abstraction","display_name":"Abstraction","score":0.547892153263092},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.4839077889919281},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.4761804938316345},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.46799132227897644},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4424929916858673},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.43735456466674805},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4164232611656189},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3627961277961731},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.1874929964542389},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11537006497383118},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.06905198097229004}],"concepts":[{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.8813759088516235},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7487142086029053},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7098225951194763},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6735371351242065},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.6402689218521118},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6176090240478516},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5510460138320923},{"id":"https://openalex.org/C124304363","wikidata":"https://www.wikidata.org/wiki/Q673661","display_name":"Abstraction","level":2,"score":0.547892153263092},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.4839077889919281},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.4761804938316345},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.46799132227897644},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4424929916858673},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.43735456466674805},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4164232611656189},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3627961277961731},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1874929964542389},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11537006497383118},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.06905198097229004},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"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/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icip46576.2022.9897868","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip46576.2022.9897868","pdf_url":null,"source":{"id":"https://openalex.org/S4363607719","display_name":"2022 IEEE International Conference on Image Processing (ICIP)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"},{"id":"pmh:oai:HAL:hal-04263872v1","is_oa":true,"landing_page_url":"https://hal.science/hal-04263872","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"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":"2022 IEEE International Conference on Image Processing (ICIP), Oct 2022, Bordeaux, France. pp.1081-1085, ⟨10.1109/ICIP46576.2022.9897868⟩","raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":{"id":"pmh:oai:HAL:hal-04263872v1","is_oa":true,"landing_page_url":"https://hal.science/hal-04263872","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"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":"2022 IEEE International Conference on Image Processing (ICIP), Oct 2022, Bordeaux, France. pp.1081-1085, ⟨10.1109/ICIP46576.2022.9897868⟩","raw_type":"info:eu-repo/semantics/conferenceObject"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1980038761","https://openalex.org/W1994530392","https://openalex.org/W2047643928","https://openalex.org/W2112759033","https://openalex.org/W2115629999","https://openalex.org/W2152161678","https://openalex.org/W2154579312","https://openalex.org/W2176287621","https://openalex.org/W2204257188","https://openalex.org/W2515866431","https://openalex.org/W2517500902","https://openalex.org/W2521616506","https://openalex.org/W2601789736","https://openalex.org/W2762769350","https://openalex.org/W2780838211","https://openalex.org/W2829067510","https://openalex.org/W2911964244","https://openalex.org/W2962217138","https://openalex.org/W2962858109","https://openalex.org/W2963363102","https://openalex.org/W2963550079","https://openalex.org/W2964231884","https://openalex.org/W2984956438","https://openalex.org/W2992070832","https://openalex.org/W3093685377","https://openalex.org/W3105577662","https://openalex.org/W4300273322","https://openalex.org/W6735519235","https://openalex.org/W6761549388"],"related_works":["https://openalex.org/W2953234277","https://openalex.org/W2626256601","https://openalex.org/W147410782","https://openalex.org/W2900413183","https://openalex.org/W4390975304","https://openalex.org/W3022252430","https://openalex.org/W4287804464","https://openalex.org/W2748667022","https://openalex.org/W3211770882","https://openalex.org/W2010629964"],"abstract_inverted_index":{"Compared":[0],"to":[1,26,37,65,76],"standard":[2],"deep":[3],"convolutional":[4],"neural":[5,16],"networks":[6,17],"(CNN)":[7],"which":[8,24],"include":[9],"a":[10,19,71],"global":[11,20],"average":[12],"pooling":[13,22,46],"operator,":[14],"second-order":[15],"have":[18,34,95],"covariance":[21,45],"operator":[23],"allows":[25],"capture":[27],"richer":[28],"statistics":[29],"of":[30,61,99],"CNN":[31,53],"features.":[32],"They":[33],"been":[35],"shown":[36],"improve":[38],"representation":[39],"and":[40,94,117],"generalization":[41],"abilities.":[42],"However,":[43],"this":[44],"is":[47,86],"performed":[48],"only":[49],"on":[50,91],"the":[51,97,100],"deepest":[52],"feature":[54],"maps.":[55],"To":[56],"benefit":[57],"from":[58],"different":[59],"levels":[60],"abstraction,":[62],"we":[63],"propose":[64],"extend":[66],"these":[67],"models":[68],"by":[69],"using":[70],"multi-layer":[72],"approach.":[73],"In":[74],"addition,":[75],"obtain":[77],"better":[78],"predictive":[79],"performance,":[80],"an":[81],"end-to-end":[82],"ensemble":[83],"learning":[84],"architecture":[85],"proposed.":[87],"Experiments":[88],"are":[89],"conducted":[90],"four":[92],"datasets":[93],"confirmed":[96],"potential":[98],"proposed":[101],"model":[102],"for":[103],"various":[104],"image":[105],"processing":[106],"applications":[107],"such":[108],"as":[109],"remote":[110],"sensing":[111],"scene":[112,115],"classification,":[113],"indoor":[114],"recognition":[116],"texture":[118],"classification.":[119]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-08-26T07:47:46.906454","created_date":"2025-10-10T00:00:00"}