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 [BibTeX] [RIS]
Decision Tree Ensemble vs. N.N. Deep Learning: Efficiency Comparison for a Small Image Dataset
Tipo de publicação: Inproceedings
Citação:
Ano: 2018
Mês: May
Publisher: Inproceedings of the 2018 International Workshop on Big Data and Information Security
Location: Jakarta, Indonesia
DOI: 10.1109/IWBIS.2018.8471704
Resumo: This paper presents a study of the efficiency of machine learning algorithms applied on an image recognition task. The dataset is composed of aerial GeoTIFF images of 5 different vineyards taken with a drone. It presents the application of two different classification algorithms with an efficiency comparison over a small dataset. A Neural Network algorithm for classification through the TensorFlow platform will be explained first, and a Decision Tree Ensemble algorithm for classification through a machine learning platform will be explained second. This work shows that the accuracy of the Decision Tree Ensemble algorithm (94.27%) outperforms the accuracy of the Deep Learning algorithm (91.22%). This result is based on the final detection accuracy as well as on the computation time.
Palavras-chave:
Autores Treboux, Jerome
Genoud, Dominique
Ingold, Rolf
Adicionado por: []
Total mark: 0
Anexos
  • IWBIS_DTEvsNNDLefficiencycompa...
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