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A New Approach to Classify Sugarcane Fields Based on Association Rules

, , , , , and . Advances in Intelligent Systems and Computing, (2018)
DOI: 10.1007/978-3-319-54978-1_61

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Supporting Computer-Aided Diagnosis and Content-Based Image Retrieval Systems through Association Rule Mining (Suporte a sistemas de auxílio ao diagnóstico e de recuperação de imagens por conteúdo usando mineração de regras de associação).. University of São Paulo, Brazil, (2008)ndltd.org (oai:agregador.ibict.br.BDTD_USP:oai:teses.usp.br:tde-16022009-144432).Improving CBIR using feature extraction based on wavelet transform., , , , and . WebMedia, page 51-58. ACM, (2008)Feature Selection Guided by Perception in Medical CBIR Systems., , , and . HISB, page 323-330. IEEE Computer Society, (2011)SACMiner: A New Classification Method Based on Statistical Association Rules to Mine Medical Images., , , and . ICEIS, volume 73 of Lecture Notes in Business Information Processing, page 249-263. Springer, (2010)Effective shape-based retrieval and classification of mammograms., , , , and . SAC, page 250-255. ACM, (2006)Adding Knowledge Extracted by Association Rules into Similarity Queries., , , , and . J. Inf. Data Manag., 1 (3): 391-406 (2010)Evaluating Boundary Conditions and Hierarchical Visualization in CBIR., , and . IV (1), page 68-73. IEEE, (2019)Mining Statistical Association Rules to Select the Most Relevant Medical Image Features., , , , and . Mining Complex Data, volume 165 of Studies in Computational Intelligence, Springer, (2009)Dimensionality reduction to improve content-based image retrieval: A clustering approach., , , and . BIBM Workshops, page 752-753. IEEE Computer Society, (2012)Statistical Association Rules and Relevance Feedback: Powerful Allies to Improve the Retrieval of Medical Images., , , and . CBMS, page 887-892. IEEE Computer Society, (2006)