In this work, we use a Multi-Layer Perceptron (MLP) artificial neural network trained with Backpropagation algorithm to perform automatic plant classification. To avoid data set bias problem, some plant data sets which use different plant features obtained by different feature extraction processes are employed. We compare MLP algorithm with several supervised learning methods from plant recognition literature using a statistical hypothesis test of type Friedman/Nemenyi test. The obtained results show the potential of MLP algorithm to deal with plant classification.
Plant Classification Using Artificial Neural Networks (july2018)
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