17 citations · 18 across the 4 of their papers we have counts for
7 papers · 1 filter
Linear Dilation-Erosion Perceptron Trained Using a Convex-Concave Procedure
Angelica Lourenço Oliveira, Marcos Eduardo Valle
Mathematical morphology (MM) is a theory of non-linear operators used for the processing and analysis of images. Morphological neural networks (MNNs) are neural networks whose neur…
Linear Dilation-Erosion Perceptron for Binary Classification
Angelica Lourenço Oliveira, Marcos Eduardo Valle
In this work, we briefly revise the reduced dilation-erosion perceptron (r-DEP) models for binary classification tasks. Then, we present the so-called linear dilation-erosion perce…
Ensemble of Binary Classifiers Combined Using Recurrent Correlation Associative Memories
Rodolfo Anibal Lobo, Marcos Eduardo Valle
An ensemble method should cleverly combine a group of base classifiers to yield an improved classifier. The majority vote is an example of a methodology used to combine classifiers…
Reduced Dilation-Erosion Perceptron for Binary Classification
Marcos Eduardo Valle
Dilation and erosion are two elementary operations from mathematical morphology, a non-linear lattice computing methodology widely used for image processing and analysis. The dilat…
Hypercomplex-Valued Recurrent Correlation Neural Networks
Marcos Eduardo Valle, Rodolfo Anibal Lobo
Recurrent correlation neural networks (RCNNs), introduced by Chiueh and Goodman as an improved version of the bipolar correlation-based Hopfield neural network, can be used to impl…
Quaternion-Valued Recurrent Projection Neural Networks on Unit Quaternions
Marcos Eduardo Valle, Rodolfo Anibal Lobo
Hypercomplex-valued neural networks, including quaternion-valued neural networks, can treat multi-dimensional data as a single entity. In this paper, we present the quaternion-valu…