Implementação de um Modelo Bag of Features para Classificação de Frutas

Authors

  • Guilherme Henrique Galelli Christmann Universidade Federal de Santa Maria
  • Fabrício Julian Carini Montenegro Universidade Federal de Santa Maria
  • Ricardo Bedin Grando Universidade Federal de Santa Maria
  • Rodrigo da Silva Guerra Universidade Federal de Santa Maria

DOI:

https://doi.org/10.5902/2448190430228

Keywords:

Ciência da Computação, Machine Learning, Visão Computacional, Frutas e Vegetais

Abstract

This work explores a classic technique in computer vision, the Bag of Features (BoF) model, in a fruit and vegetable classification problem. There’s an increasing trend in the use of Neural Networks and Deep Learning techniques applied to the automation of processes and systems. This work goes against this trend, examining how a simpler Machine Learning (ML) model would perform. For this, we defined two scenarios, one in a more controlled environment with differences only in light and objects positions, and another with more background clutter. We show that, although the trend is to use bigger and more complex ML models, simpler techniques continue to be relevant in certain scenarios.

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References

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ComInG - Communications and Innovations Gazette, Volume 02, Número 1

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Published

2018-10-22

How to Cite

Christmann, G. H. G., Montenegro, F. J. C., Grando, R. B., & Guerra, R. da S. (2018). Implementação de um Modelo Bag of Features para Classificação de Frutas. Revista ComInG - Communications and Innovations Gazette, 3(1), 70–80. https://doi.org/10.5902/2448190430228

Issue

Vol. 3 No. 1 (2018): Quarta Edição

Section

Artigos científicos

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