{"id":"https://openalex.org/W2787134274","doi":"https://doi.org/10.1109/la-cci.2017.8285727","title":"An investigation on the use of convolutional neural network for image classification in embedded systems","display_name":"An investigation on the use of convolutional neural network for image classification in embedded systems","publication_year":2017,"publication_date":"2017-11-01","ids":{"openalex":"https://openalex.org/W2787134274","doi":"https://doi.org/10.1109/la-cci.2017.8285727","mag":"2787134274"},"language":"en","primary_location":{"id":"doi:10.1109/la-cci.2017.8285727","is_oa":false,"landing_page_url":"https://doi.org/10.1109/la-cci.2017.8285727","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE Latin American Conference on Computational Intelligence (LA-CCI)","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/A5069970276","display_name":"Cec\u00edlia Fl\u00e1via da Silva","orcid":null},"institutions":[{"id":"https://openalex.org/I169045520","display_name":"Universidade Federal da Para\u00edba","ror":"https://ror.org/00p9vpz11","country_code":"BR","type":"education","lineage":["https://openalex.org/I169045520"]}],"countries":["BR"],"is_corresponding":true,"raw_author_name":"Cecilia F. Silva","raw_affiliation_strings":["Informatics Center, Federal University of Paraiba (UFPB), JooPessoa, PB, Brazil"],"affiliations":[{"raw_affiliation_string":"Informatics Center, Federal University of Paraiba (UFPB), JooPessoa, PB, Brazil","institution_ids":["https://openalex.org/I169045520"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5073203752","display_name":"Clauirton Siebra","orcid":"https://orcid.org/0000-0002-9742-2175"},"institutions":[{"id":"https://openalex.org/I169045520","display_name":"Universidade Federal da Para\u00edba","ror":"https://ror.org/00p9vpz11","country_code":"BR","type":"education","lineage":["https://openalex.org/I169045520"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Clauirton A. Siebra","raw_affiliation_strings":["Informatics Center, Federal University of Paraiba (UFPB), JooPessoa, PB, Brazil"],"affiliations":[{"raw_affiliation_string":"Informatics Center, Federal University of Paraiba (UFPB), JooPessoa, PB, Brazil","institution_ids":["https://openalex.org/I169045520"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5069970276"],"corresponding_institution_ids":["https://openalex.org/I169045520"],"apc_list":null,"apc_paid":null,"fwci":0.3641,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.70468487,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9987000226974487,"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"}},{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9977999925613403,"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/computer-science","display_name":"Computer science","score":0.8609234094619751},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.8558833599090576},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.7097334265708923},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5566099882125854},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5381048917770386},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4618149995803833},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4572541117668152},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.44427749514579773},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.4423186779022217},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.3401591181755066},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.33029818534851074}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8609234094619751},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.8558833599090576},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.7097334265708923},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5566099882125854},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5381048917770386},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4618149995803833},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4572541117668152},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.44427749514579773},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.4423186779022217},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.3401591181755066},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33029818534851074}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/la-cci.2017.8285727","is_oa":false,"landing_page_url":"https://doi.org/10.1109/la-cci.2017.8285727","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE Latin American Conference on Computational Intelligence (LA-CCI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.4300000071525574}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W345900524","https://openalex.org/W1677409904","https://openalex.org/W1686810756","https://openalex.org/W1968422655","https://openalex.org/W2031067224","https://openalex.org/W2034978228","https://openalex.org/W2067713319","https://openalex.org/W2094756095","https://openalex.org/W2095705004","https://openalex.org/W2108069432","https://openalex.org/W2125085157","https://openalex.org/W2137871902","https://openalex.org/W2152175008","https://openalex.org/W2155893237","https://openalex.org/W2161969291","https://openalex.org/W2271840356","https://openalex.org/W2285788670","https://openalex.org/W2334805829","https://openalex.org/W2522025381","https://openalex.org/W2537632740","https://openalex.org/W2555371250","https://openalex.org/W2598842688","https://openalex.org/W2736230459","https://openalex.org/W2740815424","https://openalex.org/W2950094539","https://openalex.org/W2962835968","https://openalex.org/W6637373629","https://openalex.org/W6674330103","https://openalex.org/W6735809762"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W4321487865","https://openalex.org/W2952813363","https://openalex.org/W4360783045","https://openalex.org/W2963346891","https://openalex.org/W3176438653","https://openalex.org/W2770149305","https://openalex.org/W3167930666","https://openalex.org/W3014952856","https://openalex.org/W3010730661"],"abstract_inverted_index":{"The":[0,33,82],"study":[1],"of":[2,24,35,57,70,84,99],"Convolutional":[3],"Neural":[4],"Network":[5],"(CNN)":[6],"for":[7],"image":[8],"classification":[9,91],"is":[10,38,93],"basically":[11],"carried":[12],"out":[13],"on":[14,30],"high":[15],"performance":[16,69],"and":[17,50,66,78],"parallel":[18],"platforms,":[19],"so":[20],"that":[21,43,62,89],"the":[22,25,55,58,68,96,100],"results":[23,56,83,98],"literature":[26],"cannot":[27],"be":[28],"replied":[29],"embedded":[31],"systems.":[32],"aim":[34],"our":[36,85],"work":[37],"to":[39,95],"investigate":[40],"CNN":[41,72],"architectures":[42],"can":[44],"run":[45],"in":[46],"such":[47],"limited":[48],"platforms":[49],"still":[51],"maintain":[52],"or":[53],"improve":[54],"current":[59],"approaches.":[60],"To":[61],"end,":[63],"we":[64],"specify":[65],"evaluate":[67],"several":[71],"frameworks":[73],"using":[74,103],"different":[75],"network":[76],"configurations":[77],"dataset":[79],"pre-processing":[80],"techniques.":[81],"final":[86],"approach":[87],"show":[88],"its":[90],"efficiency":[92],"close":[94],"best":[97],"literature,":[101],"however":[102],"a":[104],"much":[105],"lower":[106],"computational":[107],"power.":[108]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}