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Nature-inspired optimum-path forest
(2021-01-01)
The Optimum-Path Forest (OPF) is a graph-based classifier that models pattern recognition problems as a graph partitioning task. The OPF learning process is performed in a competitive fashion where a few key samples (i.e., ...
Optimizing Contextual-Based Optimum-Forest Classification through Swarm Intelligence
(Springer, 2013-01-01)
Several works have been conducted in order to improve classification problems. However, a considerable amount of them do not consider the contextual information in the learning process, which may help the classification ...
Optimizing contextual-based optimum-forest classification through swarm intelligence
(2013-01-01)
Several works have been conducted in order to improve classification problems. However, a considerable amount of them do not consider the contextual information in the learning process, which may help the classification ...
Optimizing and validating the Gravitational Process Path model for regional debris-flow runout modelling
(Copernicus GmbH, 2021)
© 2021 The Author(s).Knowing the source and runout of debris flows can help in planning strategies aimed at mitigating these hazards. Our research in this paper focuses on developing a novel approach for optimizing runout ...
A path- and label-cost propagation approach to speedup the training of the optimum-path forest classifier
(Elsevier B.V., 2014-04-15)
In general, pattern recognition techniques require a high computational burden for learning the discriminating functions that are responsible to separate samples from distinct classes. As such, there are several studies ...
A comparison about evolutionary algorithms for optimum-path forest clustering optimization
(2013)
In this paper we deal with the problem of boosting the Optimum-Path Forest (OPF) clustering approach using evolutionary-based optimization techniques. As the OPF classifier performs an exhaustive search to find out the ...
A path- and label-cost propagation approach to speedup the training of the optimum-path forest classifier
(Elsevier Science BvAmsterdamHolanda, 2014)
Predicting optimal solution costs with bidirectional stratified sampling in regular search spaces
(Artificial Intelligence, 2018)
Improving image classification through descriptor combination
(2012-12-01)
The efficiency in image classification tasks can be improved using combined information provided by several sources, such as shape, color, and texture visual properties. Although many works proposed to combine different ...
Improving image classification through descriptor combination
(2012-12-01)
The efficiency in image classification tasks can be improved using combined information provided by several sources, such as shape, color, and texture visual properties. Although many works proposed to combine different ...