Leonardo R. Emmendorfer - researchr alias

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Viewing Publication 1 - 15 from 15

2022

On the Evaluation of Two Methods Applied to the Morphometry of Linear DunesTatiana Taís Schein, Leonardo R. Emmendorfer, Fabiano NobreMendes, Bárbara D. A. Rodriguez, Luis Pedro Melo de Almeida, Vinícius Menezes de Oliveira. iciap 2022: 473-479 [doi]

2021

Explainable Classification Methods for Fish Species Detection Using Hydroacoustic DataLucas T. Bonifácio, Giancarlo Lucca, Graçaliz Pereira Dimuro, Eduardo N. Borges, Leonardo R. Emmendorfer, Stefan Cruz Weigert. fuzzIEEE 2021: 1-6 [doi]

2020

A Conservative Sharpening Filter for Interpolated ImagesLeonardo R. Emmendorfer. sibgrapi 2020: 93-100 [doi]

A multi-agent-based algorithm for data clusteringLutiele M. Godois, Diana Francisca Adamatti, Leonardo R. Emmendorfer. pai, 9(4):305-313, 2020. [doi]

2017

A Study on the Relationship between Internal and External Validity Indices Applied to Partitioning and Density-based Clustering AlgorithmsCaroline Tomasini, Eduardo Nunes Borges, Karina Machado, Leonardo R. Emmendorfer. ICEIS 2017: 89-98 [doi]

2016

A methodology for selecting the most suitable cluster validation internal indicesCaroline Tomasini, Leonardo R. Emmendorfer, Eduardo Nunes Borges, Karina Machado. SAC 2016: 901-903 [doi]

2014

Including operator's skill and environment conditions in IMSSilvia S. C. Botelho, Nelson Duarte Filho, Danúbia Bueno Espíndola, Marcos Amaral, Leonardo R. Emmendorfer, Rafael Penna, Enzo Morosini Frazzon, Carlos Eduardo Pereira, Renato Ventura Henriques. indin 2014: 295-300 [doi]

2013

Inference of Genetic Regulatory Networks Using an Estimation of Distribution AlgorithmThyago Salvá, Leonardo R. Emmendorfer, Adriano Velasque Werhli. wob 2013: 148-159 [doi]

2010

On the Design of Populational ClusteringLeonardo R. Emmendorfer. ijcci 2010: 289-292

2009

Effective Linkage Learning Using Low-Order Statistics and ClusteringLeonardo R. Emmendorfer, Aurora Pozo. tec, 13(6):1233-1246, 2009. [doi]

2008

Selecting software reliability models with a neural network meta classifierRafael Caiuta, Aurora Pozo, Leonardo R. Emmendorfer, Silvia Regina Vergilio. ijcnn 2008: 3747-3754 [doi]

A Clustering-Based Approach for Linkage Learning Applied to Multimodal OptimizationLeonardo R. Emmendorfer, Aurora Pozo. In Ying-Ping Chen, Meng-Hiot Lim, editors, Linkage in Evolutionary Computation. Volume 157 of Studies in Computational Intelligence, pages 225-248, Springer, 2008. [doi]

2007

An empirical evaluation of linkage learning strategies for multimodal optimizationLeonardo R. Emmendorfer, Aurora Trinidad Ramirez Pozo. cec 2007: 326-333 [doi]

An Incremental Approach for Niching and Building Block Detection via ClusteringLeonardo R. Emmendorfer, Aurora Trinidad Ramirez Pozo. isda 2007: 303-308 [doi]

2005

Using Prior Knowledge to Improve the Performance of an Estimation of Distribution Algorithm Applied to Feature SelectionLeonardo R. Emmendorfer, Rodrigo Traleski, Aurora Trinidad Ramirez Pozo. his 2005: 393-398 [doi]

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