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Supervised pattern classification based on optimum‐path forest
TLDR
We present a supervised classification method which represents each class by one or more optimum‐path trees rooted at some key samples, called prototypes. Expand
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A genetic programming framework for content-based image retrieval
TLDR
The effectiveness of content-based image retrieval (CBIR systems can be improved by combining image features or by weighting image similarities, as computed from multiple feature vectors. Expand
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BBA: A Binary Bat Algorithm for Feature Selection
TLDR
Feature selection aims to find the most important information from a given set of features. Expand
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A New Approach for Nontechnical Losses Detection Based on Optimum-Path Forest
Nowadays, fraud detection is important to avoid nontechnical energy losses. Various electric companies around the world have been faced with such losses, mainly from industrial and commercialExpand
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BCS: A Binary Cuckoo Search algorithm for feature selection
Feature selection has been actively pursued in the last years, since to find the most discriminative set of features can enhance the recognition rates and also to make feature extraction faster. InExpand
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A wrapper approach for feature selection based on Bat Algorithm and Optimum-Path Forest
TLDR
We present a wrapper feature selection approach based on Bat Algorithm (BA) and Optimum-Path Forest (OPF), in which we model the problem of feature selection as an binary-based optimization technique, guided by BA using the OPF accuracy over a validating set as the fitness function to be maximized. Expand
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Handwritten dynamics assessment through convolutional neural networks: An application to Parkinson's disease identification
TLDR
We introduce convolutional neural networks to learn features from images produced by handwritten dynamics, which capture different information during the assessment, which can be useful for automatic Parkinson's disease identification. Expand
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Improving Parkinson's disease identification through evolutionary-based feature selection
TLDR
We deal with the problem of feature selection in the context of Parkinson’s disease automatic identification using evolutionary-based techniques in order to find the subset of features that maximize the accuracy of the Optimum-Path Forest classifier. Expand
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Computational methods for pigmented skin lesion classification in images: review and future trends
TLDR
An overview of the main and current computational methods that have been proposed for pattern analysis and pigmented skin lesion classification. Expand
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Spoken emotion recognition through optimum-path forest classification using glottal features
TLDR
A new method for the recognition of spoken emotions is presented based on features of the glottal airflow signal. Expand
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