المؤلفون: Lucas Galvão, Otto Pires, Yan Alef Chagas, Maria Heloísa Fraga, Marcelo A. Moret

المصدر: Vetor, Vol 34, Iss 2 (2024)

مصطلحات موضوعية: Seleção de características, Dados financeiros, Quantum Annealing, QUBO, Aprendizado de Máquina, Engineering (General). Civil engineering (General), TA1-2040, Mathematics, QA1-939

وصف الملف: electronic resource

Relation: https://furg.emnuvens.com.br/vetor/article/view/18358; https://doaj.org/toc/0102-7352; https://doaj.org/toc/2358-3452

URL الوصول: https://doaj.org/article/ddd77a95acd74c108dfbf86be069cf6b

المؤلفون: Alves, Victor, Cury, Alexandre

المصدر: Principia: Caminhos da Iniciação Científica; v. 23 (2023) ; 2179-3700 ; 1518-2983

مصطلحات موضوعية: Monitoramento da Saúde Estrutural, Localização de Dano, Seleção de Características, Multi-domínio, Automático

وصف الملف: application/pdf

Relation: https://periodicos.ufjf.br/index.php/principia/article/view/40261/27178; https://periodicos.ufjf.br/index.php/principia/article/view/40261

الاتاحة: https://periodicos.ufjf.br/index.php/principia/article/view/40261

المؤلفون: Nogueira, Adara Stéfanny Rodrigues

المساهمون: Ferreira, Artur Jorge, RCIPL

مصطلحات موضوعية: Seleção de características, Discretização de características, Dados de microarray, Cancro, Explicabilidade da classificação, Feature selection, Feature discretization, Microarray data, Cancer, Explainability of classification

وصف الملف: application/pdf

Relation: NOGUEIRA, Adara Stéfanny Rodrigues - Clinical data mining and classification. Lisboa: Instituto Superior de Engenharia de Lisboa, 2022. Dissertação de Mestrado.

الاتاحة: http://hdl.handle.net/10400.21/16504

المؤلفون: Gomes, Henrique Manuel Carvalho

المساهمون: Datia, Nuno Miguel Soares, Pato, Matilde Pós-de-Mina, RCIPL

مصطلحات موضوعية: Seleção de características, Mineração de dados, Avaliação de características, Filtros, Conjunto de filtros, Feature selection, Data mining, Feature ranking, Filters, Filter ensemble

وصف الملف: application/pdf

Relation: GOMES, Henrique Manuel Carvalho – Desenvolvimento de um package em R para Ensemble Feature Ranking – EFR. Lisboa: Instituto Superior de Engenharia de Lisboa, 2021. Dissertação de Mestrado.

الاتاحة: http://hdl.handle.net/10400.21/14229

المؤلفون: Galvão, Lucas, Pires, Otto, Chagas, Yan Alef, Fraga, Maria Heloísa, Moret, Marcelo A.

المصدر: VETOR - Journal of Exact Sciences and Engineering; Vol. 34 No. 2 (2024); e18358 ; VETOR - Revista de Ciências Exatas e Engenharias; v. 34 n. 2 (2024); e18358 ; 2358-3452 ; 0102-7352

مصطلحات موضوعية: Feature selection, Financial Data, Quantum Annealing, QUBO, Machine Learning, Computational modeling, Seleção de características, Dados financeiros, Aprendizado de Máquina, Modelagem computacional

وصف الملف: application/pdf

Relation: https://periodicos.furg.br/vetor/article/view/18358/11438; https://periodicos.furg.br/vetor/article/view/18358

الاتاحة: https://periodicos.furg.br/vetor/article/view/18358

المؤلفون: Chitongua, Fátima Joana Dantas Gonçalves

المساهمون: Pais, Sebastião Augusto Rodrigues Figueiredo, Cordeiro, João Paulo da Costa, uBibliorum

مصطلحات موضوعية: Corpora, Extração de Termos Relevantes, Seleção de Características, Domínio/Área Científica::Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática

وصف الملف: application/pdf

الاتاحة: http://hdl.handle.net/10400.6/9937

المؤلفون: Silva, Maxwell Esdra Acioli, Holanda, Victor Gabriel Lima, Silva, Rodrigo Santos da, Severiano, Paulo Victor Laurentino, Silva, Rafael de Amorim

المصدر: Journal of Health Informatics; Vol. 12 (2020): Suplemento I - XVII Congresso Brasileiro de Informática em Saúde - CBIS 2020 ; Journal of Health Informatics; v. 12 (2020): Suplemento I - XVII Congresso Brasileiro de Informática em Saúde - CBIS 2020 ; 2175-4411

مصطلحات موضوعية: Seleção de características, Métodos, Prognóstico Câncer

وصف الملف: application/pdf

Relation: https://jhi.sbis.org.br/index.php/jhi-sbis/article/view/817/420; https://jhi.sbis.org.br/index.php/jhi-sbis/article/view/817

الاتاحة: https://jhi.sbis.org.br/index.php/jhi-sbis/article/view/817

المؤلفون: Silva, Gabriela Oliveira Mota da

المساهمون: Durão, Frederico Araújo, orcid:0000-0002-7766-6666, http://lattes.cnpq.br/6271096128174325, Lino, Natasha Correia Queiroz, orcid:0000-0002-8131-0566, http://lattes.cnpq.br/7853125713114677, Oliveira Neto, Rosalvo Ferreira de, orcid:0000-0002-3290-5539, http://lattes.cnpq.br/9548186939653024, Claro, Daniela Barreiro, orcid:0000-0001-8586-1042, http://lattes.cnpq.br/9217378047217370, Salvador, Laís do Nascimento, orcid:0000-0001-7441-057X, https://lattes.cnpq.br/1972531466861737

مصطلحات موضوعية: Sistemas de recomendação, Dados abertos conectados, Similaridade semântica, Personalização, Seleção de características, Recommender systems, Linked open data, Semantic similarity, Personalization, Feature selection, CNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO::METODOLOGIA E TECNICAS DA COMPUTACAO

وصف الملف: application/pdf

Relation: ADOMAVICIUS, G.; TUZHILIN; ALEXANDER. Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions. IEEE Transactions on Knowledge and Data Engineering, Institute of Electrical and Electronics Engineers (IEEE), v. 17, n. 6, p. 734–749, jun 2005. AGGARWAL, C. C. Recommender systems: the textbook. [S.l.]: Springer International Publishing, 2016. ANGLES, R.; GUTIERREZ, C. The expressive power of sparql. In: SPRINGER. International Semantic Web Conference. [S.l.], 2008. p. 114–129. BARMAN, A.; TEWARI, A. S. Collaborative recommendation system using dynamic content based filtering, association rule mining and opinion mining. International Journal of Intelligent Engineering and Systems, The Intelligent Networks and Systems Society, v. 10, n. 5, p. 57–66, oct 2017. BERNERS-LEE, T. Linked-data design issues. w3c design issue document. The WorldWide Web Consortium W3C, 2009. BERNERS-LEE, T. Design issues: Linked data (2006). URL http://www.w3.org/DesignIssues/LinkedData.html, 2011. BERNERS-LEE, T.; FIELDING, R.; MASINTER, L. Rfc 3986. Uniform Resource Identifier (URI): Generic Syntax, InternetEngineering Task Force, 2005. BERNERS-LEE, T. et al. The semantic web. Scientific american, New York, NY, USA:, v. 284, n. 5, p. 28–37, 2001. BIZER, C.; HEATH, T.; Berners-Lee, T. Linked data - the story so far. Int. J. Semantic Web Inf. Syst., v. 5, n. 3, p. 1–22, 2009. BIZER, C.; HEATH, T.; BERNERS-LEE, T. Linked data-the story so far. Semantic services, interoperability and web applications: emerging concepts, p. 205–227, 2009. BRICKLEY, D.; MILLER, L. FOAF Vocabulary Specification. [S.l.], 2004. Http://xmlns.com/foaf/0.1/. URL: . BURKE, R. Hybrid recommender systems: Survey and experiments. User Modeling and User-Adapted Interaction, Kluwer Academic Publishers, Hingham, MA, USA, v. 12, n. 4, p. 331–370, nov. 2002. ISSN 0924-1868. CAO, Y. et al. Unifying knowledge graph learning and recommendation: Towards a better understanding of user preferences. In: The World Wide Web Conference. New York, NY, USA: Association for Computing Machinery, 2019. (WWW ’19), p. 151–161. ISBN 9781450366748. URL: . CATHERINE, R.; COHEN, W. Personalized recommendations using knowledge graphs: A probabilistic logic programming approach. In: Proceedings of the 10th ACM Conference on Recommender Systems. New York, NY, USA: ACM, 2016. (RecSys ’16), p. 325–332. ISBN 978-1-4503-4035-9. CHENIKI, N. et al. Lods: A linked open data based similarity measure. 2016 IEEE 25th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE), p. 229–234, 2016. CODINA, V.; RICCI, F.; CECCARONI, L. Exploiting the Semantic Similarity of Contextual Situations for Pre-filtering Recommendation. [S.l.]: Springer, Berlin, Heidelberg, 2013. CONTRIBUTORS, D. How to edit the dbpedia ontology. In: . DBpedia Mappings. DBpedia.org, 2022. URL: . Acesso em: March 9th, 2022. DAVOODI, E.; KIANMEHR, K.; AFSHARCHI, M. A semantic social network-based expert recommender system. Applied Intelligence, Springer Nature, v. 39, n. 1, p. 1–13, oct 2013. ISSN 1573-7497. DIETZ, J. L. What is Enterprise Ontology? [S.l.]: Springer, 2006. DU, Y. et al. Post-hoc recommendation explanations through an efficient exploitation of the dbpedia category hierarchy. Knowledge-Based Systems, v. 245, p. 108560, 2022. ISSN 0950-7051. URL: . FERRÉ, S. Sparklis: a sparql endpoint explorer for expressive question answering. In: ISWC posters & demonstrations track. [S.l.: s.n.], 2014. FIELDING, R. et al. Hypertext transfer protocol–HTTP/1.1. [S.l.], 1999. FRESSATO, E. P. Incorporação de metadados semânticos para recomendação no cenário de partida fria. 105 p. Tese (Doutorado) — Universidade de São Paulo, 2019. GAN, L. et al. Emdkg: Improving accuracy-diversity trade-off in recommendation with em-based model and knowledge graph embedding. In: IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology. New York, NY, USA: Association for Computing Machinery, 2021. (WI-IAT ’21), p. 17–24. ISBN 9781450391153. URL: . GARCÍA, C. G. et al. Social recommender system: A recommender system based on tweets for points of interest. In: Proceedings of the 4th Multidisciplinary International Social Networks Conference on ZZZ - MISNC '17. New York, NY, USA: ACM Press, 2017. (MISNC ’17), p. 28:1–28:7. ISBN 978-1-4503-4881-2. GARSHOL, L. M. Living with topic maps and rdf. Online only, Citeseer, v. 13, 2003. GEMMIS, M. de et al. Semantics-aware content-based recommender systems. In: RICCI, F.; ROKACH, L.; SHAPIRA, B. (Ed.). Recommender Systems Handbook. Boston, MA: Springer US, 2015. p. 119–159. ISBN 978-1-4899-7637-6. GRUBER, T. R. Toward principles for the design of ontologies used for knowledge sharing? International journal of human-computer studies, Elsevier, v. 43, n. 5-6, p. 907–928, 1995. GUHA, R.; BRICKLEY, D. W3C Recommendation, RDF Schema 1.1. 2014. URL: . GUO, G. Resolving data sparsity and cold start in recommender systems. In: MASTHOFF, J. et al. (Ed.). User Modeling, Adaptation, and Personalization. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. p. 361–364. ISBN 978-3-642-31454-4. GUO, S.; ALAMUDUN, F.; HAMMOND, T. Résumatcher: A personalized résumé-job matching system. Expert Systems with Applications, Elsevier, v. 60, p. 169–182, 2016. GUY, I. People recommendation on social media. In: . Social Information Access: Systems and Technologies. Cham: Springer International Publishing, 2018. p. 570–623. ISBN 978-3-319-90092-6. GUYON, I.; ELISSEEFF, A. An introduction to variable and feature selection. J. Mach. Learn. Res., JMLR.org, v. 3, p. 1157–1182, mar. 2003. ISSN 1532-4435. HERLOCKER, J. L. et al. Evaluating collaborative filtering recommender systems. ACM Transactions on Information Systems, Association for Computing Machinery (ACM), v. 22, n. 1, p. 5–53, jan 2004. HOLZE, J. Dbpedia snapshot 2022-12 release. In: . DBpedia Archive: Announcement. DBpedia.org, 2023. URL: . Acesso em: March 27th, 2023. HUTT, K. A comparison of rdf query languages. In: Proc. of 21th Computer Science Seminar, Hartfort, Connecticut. [S.l.: s.n.], 2005. p. 1–7. ISINKAYE, F.; FOLAJIMI, Y.; OJOKOH, B. Recommendation systems: Principles, methods and evaluation. Egyptian Informatics Journal, Elsevier BV, v. 16, n. 3, p. 261– 273, nov 2015. JäRVELIN, K.; KEKäLäINEN, J. Cumulated gain-based evaluation of ir techniques. ACM Trans. Inf. Syst., ACM, New York, NY, USA, v. 20, n. 4, p. 422–446, out. 2002. ISSN 1046-8188. JAWAHEER, G.; WELLER, P.; KOSTKOVA, P. Modeling user preferences in recommender systems: A classification framework for explicit and implicit user feedback. ACM Transactions on Interactive Intelligent Systems, Association for Computing Machinery (ACM), v. 4, n. 2, p. 1–26, jun 2014. JOSEPH, K.; JIANG, H. Content based news recommendation via shortest entity distance over knowledge graphs. In: Companion Proceedings of The 2019 World Wide Web Conference. New York, NY, USA: ACM, 2019. (WWW ’19), p. 690–699. ISBN 978-1- 4503-6675-5. KAUFMAN, L.; ROUSSEEUW, P. J. Finding Groups in Data: An Introduction to Cluster Analysis. [S.l.]: John Wiley, 1990. ISBN 978-0-47031680-1. KIM, M. H. J. G. 5(star) open data. In: . 5stardata.info. Content freely available under the CC0 Public Domain Dedication, 2019. URL: . Acesso em: June 6th, 2019. KLUVER, D.; EKSTRAND, M. D.; KONSTAN, J. A. Rating-based collaborative filtering: Algorithms and evaluation. In: . Social Information Access. [S.l.]: Springer International Publishing, 2018. cap. 10, p. 344–390. ISBN 978-3-319-90092-6. KLYNE, G.; CARROLL, J. J. Resource description framework (rdf): Concepts and abstract syntax. 2006. KOBILAROV, G. et al. Media meets semantic web - how the bbc uses dbpedia and linked data to make connections. In: ESWC. [S.l.: s.n.], 2009. KUMAR, P.; THAKUR, R. S. Recommendation system techniques and related issues: a survey. International Journal of Information Technology, Springer Nature, v. 10, n. 4, p. 495–501, apr 2018. LAM, X. N. et al. Addressing cold-start problem in recommendation systems. In: Proceedings of the 2Nd International Conference on Ubiquitous Information Management and Communication. New York, NY, USA: ACM, 2008. (ICUIMC ’08), p. 208–211. ISBN 978-1-59593-993-7. LEHMANN, J. et al. DBpedia - a large-scale, multilingual knowledge base extracted from wikipedia. Semantic Web Journal, v. 6, n. 2, p. 167–195, 2015. URL: . LÜ, L. et al. Recommender systems. Physics Reports, Elsevier BV, v. 519, n. 1, p. 1–49, oct 2012. MANNING, C. D.; RAGHAVAN, P.; SCHÜTZE, H. Introduction to Information Retrieval. New York, NY, USA: Cambridge University Press, 2008. ISBN 0521865719, 9780521865715. MANNING, C. D.; RAGHAVAN, P.; SCHüTZE, H. Evaluation in information retrieval. In: . Introduction to Information Retrieval. [S.l.]: Cambridge University Press, 2008. p. 139–161. MCCRAE, J. P. The linked open data cloud. In: . The Linked Open Data Cloud. Insight Centre for Data Analytics, 2023. URL: . Acesso em: September 3rd, 2023. MUSTO, C. et al. Semantics-aware graph-based recommender systems exploiting linked open data. In: Proceedings of the 2016 Conference on User Modeling Adaptation and Personalization. New York, NY, USA: ACM, 2016. (UMAP ’16), p. 229–237. ISBN 978- 1-4503-4368-8. NATARAJAN, S. et al. Cd-semmf: Cross-domain semantic relatedness based matrix factorization model enabled with linked open data for user cold start issue. IEEE Access, v. 10, p. 52955–52970, 2022. URL: . NOIA, T. D. et al. 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Alleviating the data sparsity problem of recommender systems by clustering nodes in bipartite networks. Expert Systems with Applications, v. 149, p. 113346, 2020. ISSN 0957-4174. URL: . ZHANG, Z.-K. et al. Solving the cold-start problem in recommender systems with social tags. EPL (Europhysics Letters), IOP Publishing, v. 92, n. 2, p. 28002, oct 2010.; https://repositorio.ufba.br/handle/ri/39279

الاتاحة: https://repositorio.ufba.br/handle/ri/39279

المؤلفون: Kwiatkowska, Katarzyna Malgorzata

المساهمون: Falcão, André Osório e Cruz de Azerêdo, 1969-, Sousa, Lisete Maria Ribeiro de, 1972-, Repositório da Universidade de Lisboa

مصطلحات موضوعية: Aprendizagem automática, Modelo preditivo, Seleção de características, Integração de dados, Teses de mestrado - 2017, Departamento de Informática

وصف الملف: application/pdf

الاتاحة: http://hdl.handle.net/10451/31940

المؤلفون: Sousa, Kleyson Morais de

المساهمون: Carvalho, Rafael Lima de

مصطلحات موضوعية: Seleção de características, Otimização, Aprendizagem de Máquina, Enxame de Partículas, CNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO

وصف الملف: application/pdf

Relation: SOUSA, Kleyson Morais de. Utilização de algoritmos de otimização por enxame aplicados à seleção de características. 52f. Monografia (Graduação) - Ciência da computação, Universidade Federal do Tocantins, Palmas, 2020.; http://hdl.handle.net/11612/3235

الاتاحة: http://hdl.handle.net/11612/3235

المؤلفون: Tavares, Samuel Alves

المساهمون: Costa, André Luiz Aguiar da, http://lattes.cnpq.br/7455660237808982, Silva, Ederson Rosa da, http://lattes.cnpq.br/0745957106999584, Mateus, Alexandre Coutinho, http://lattes.cnpq.br/5723816513897339

مصطلحات موضوعية: Aprendizado de máquina, Machine learning, Classificação automática de modulações, Automatic modulation classification, Inteligência artificial, Artificial intelligence, Canal de rayleigh, Rayleigh channel, Correlação, Correlation, Seleção de características, Feature selection, CNPQ::ENGENHARIAS::ENGENHARIA ELETRICA::TELECOMUNICACOES

وصف الملف: application/pdf

Relation: TAVARES, Samuel Alves. Otimização de características para classificação automática de modulação de sinais afetados pelos canais Awgn e Rayleigh. 2022. 56 f. Trabalho de Conclusão de Curso (Graduação em Engenharia Eletrônica e de Telecomunicações) – Universidade Federal de Uberlândia, Uberlândia, 2023.; https://repositorio.ufu.br/handle/123456789/37275

الاتاحة: https://repositorio.ufu.br/handle/123456789/37275

المؤلفون: Sementille, Luiz Fernando Merli de Oliveira

المساهمون: Universidade Estadual Paulista (UNESP)

مصطلحات موضوعية: Aplicação web, Seleção de características, Meta-heurística, Web application, Feature selection, Metaheuristic

Relation: http://hdl.handle.net/11449/239156

الاتاحة: http://hdl.handle.net/11449/239156

المؤلفون: Teodoro, Felipe Gustavo Silva

Thesis Advisors: Lima, Clodoaldo Aparecido de Moraes

مصطلحات موضوعية: Algoritmo genético, Algoritmo memético, Biomedical biometri, Biometria biomédica, Biometric systems, Eletrocardiograma, Feature selection, Genetic algorithm, Memetic algorithm, Pattern recognition, Reconhecimento de padrões, Seleção de características

وصف الملف: application/pdf

الاتاحة: http://www.teses.usp.br/teses/disponiveis/100/100131/tde-19122016-003653/

المؤلفون: Jorge, Fábio Rodrigues

Thesis Advisors: Ponti, Moacir Antonelli

مصطلحات موضوعية: Aprendizado de máquina, Bases desbalanceadas, Extração de características, Feature extraction, Feature selection, Machine learning, Remote sensing, Seleção de características, Sensoriamento remoto, Unbalanced bases

وصف الملف: application/pdf

الاتاحة: http://www.teses.usp.br/teses/disponiveis/55/55134/tde-14092015-100714/

المؤلفون: Silva, Felipe Leno da

Thesis Advisors: Costa, Anna Helena Reali

مصطلحات موضوعية: Aprendizado supervisionado, Aprendizagem de máquina, Articial intelligence, Bee species recognition, Classificação de abelhas, Computer vision, Extração de características, Feature extraction, Feature selection., Inteligência articial, Machine learning, Pattern recognition, Reconhecimento de padrões, Seleção de características, Supervised learning, Visão computacional

وصف الملف: application/pdf

الاتاحة: http://www.teses.usp.br/teses/disponiveis/3/3141/tde-19102015-145442/

المؤلفون: Terrematte, Patrick Cesar Alves

المساهمون: Doria Neto, Adrião Duarte, http://lattes.cnpq.br/4283045850342312, orcid:0000-0002-5445-7327, http://lattes.cnpq.br/1987295209521433, Ferreira, Beatriz Stransky, orcid:0000-0003-4506-393X, http://lattes.cnpq.br/3142264445097872, Leite, Cicilia Raquel Maia, Araújo, Daniel Sabino Amorim de, http://lattes.cnpq.br/4744754780165354, Assumpção, Paulo Pimentel de, Sakamoto, Tetsu

مصطلحات موضوعية: Aprendizagem de máquina, Bioinformática, Câncer renal, Assinatura genética, Seleção de características, Informação mútua

وصف الملف: application/pdf

Relation: TERREMATTE, Patrick Cesar Alves. Uma nova assinatura de 13 genes via aprendizagem de máquina para predição de sobrevida de pacientes com carcinoma renal de células clara. 2022. 72f. Tese (Doutorado em Bioinformática) - Instituto Metrópole Digital, Universidade Federal do Rio Grande do Norte, Natal, 2022.; https://repositorio.ufrn.br/handle/123456789/48273

الاتاحة: https://repositorio.ufrn.br/handle/123456789/48273

المؤلفون: Erick Nilsen Pereira Souza, Daniela Barreiro Claro

المصدر: Linguamática, Vol 6, Iss 2 (2014)

مصطلحات موضوعية: Extração de Relações Abertas, Seleção de Características, Language and Literature, Philology. Linguistics, P1-1091

وصف الملف: electronic resource

Relation: http://linguamatica.com/index.php/linguamatica/article/view/182; https://doaj.org/toc/1647-0818

URL الوصول: https://doaj.org/article/17d809492bde43d1a7525a01eda44339

المؤلفون: Silverio, Priscilla Suene de Santana Nogueira

المساهمون: Oliveira, Amanda Gondim de, Canuto, Anne Magaly de Paula, Santos, Araken de Medeiros, Lima, João Paulo Matos Santos, Oliveira, Laura Emmanuella Alves dds Santos Santana de, Barbosa, Euzébio Guimarães

المصدر: Repositório Institucional da UFRN
Universidade Federal do Rio Grande do Norte (UFRN)
instacron:UFRN

مصطلحات موضوعية: Seleção de características, Bioinformática estrutural, QSAR-3D, Predição, Quimioinformática, Atividade biológica, Modelos QSAR, Regressão

URL الوصول: https://explore.openaire.eu/search/publication?articleId=od______3056::c5d9f12fffc5d8cbe5bd98c786aebb93
https://repositorio.ufrn.br/handle/123456789/44668

المؤلفون: Santos, Rosiane Correia

Thesis Advisors: Oliveira, Patrícia Rufino

مصطلحات موضوعية: Algoritmos genéticos, Aprendizado supervisionado, Classical planning, Feature selection, Genetic algorithms, Multilayer perceptron network, Neural networks, Planejamento clássico, Rede perceptron multicamadas, Redes neurais artificiais, Seleção de características, Supervised learning

وصف الملف: application/pdf

الاتاحة: http://www.teses.usp.br/teses/disponiveis/100/100131/tde-25012014-115621/

المؤلفون: Mamani, Gabriel Efrain Humpire

Thesis Advisors: Traina, Agma Juci Machado

مصطلحات موضوعية: CAD, CBIR, Extração de características, Feature extraction, Feature selection, Seleção de características

وصف الملف: application/pdf

الاتاحة: http://www.teses.usp.br/teses/disponiveis/55/55134/tde-20022013-095418/