Optimum-Path Forest in the classification of defects in Bovine Leather
| Autor: | Marcelo Henriques de Carvalho, C B Pache Marcio, Willian Paraguassu Amorim, Hemerson Pistori, Felipe Silveira Brito Borges |
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| Rok vydání: | 2019 |
| Předmět: |
Artificial neural network
Computer science business.industry Computer Science::Neural and Evolutionary Computation Feature extraction Decision tree Pattern recognition Support vector machine ComputingMethodologies_PATTERNRECOGNITION C4.5 algorithm Path (graph theory) Classifier (linguistics) Graph (abstract data type) Artificial intelligence business |
| Zdroj: | 2019 XV Workshop de Visão Computacional (WVC). |
| DOI: | 10.1109/wvc.2019.8876936 |
| Popis: | In this paper, the Optimum-Path Forest (OPF) classifier is applied in the classification of defects in cowhide, a problem of great evaluation complexity. The OPF classifier reduces a pattern classification problem to the problem of partitioning the vertices of a graph induced by its data set. The results revealed a competent performance compared to traditional classifiers, such as Support Vector Machines (SVM), Artificial Neural Networks-Perceptron Multilayer (MLP), Decision Trees (J48) and k-Nearest Neighbor (kNN). |
| Databáze: | OpenAIRE |
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