TRIST: TREE RECOGNITION INTELLIGENT SYSTEM

Authors

  • Laura ONAC Faculty of Mathematics and Computer Science, Babeș-Bolyai University, Cluj-Napoca, Romania. Email address: olic1770@scs.ubbcluj.ro

DOI:

https://doi.org/10.24193/subbi.2019.1.01

Keywords:

machine learning, computer vision, convolutional neural networks, image classification, leaf recognition.

Abstract

Plant recognition represents a challenging computer vision problem due to the great variations of shape and texture among plant organs, within the same species. This paper proposes a light-weight, but reasonably deep Convolutional Neural Network architecture able to carry out this classification task. Multiple experiments were conducted with the proposed network architecture on the MEW2012 and Swedish leaf datasets. The experiments showed promising results, outperforming the current state-of-the-art systems that rely exclusively on a convolutional network for plant classification.

Author Biography

Laura ONAC, Faculty of Mathematics and Computer Science, Babeș-Bolyai University, Cluj-Napoca, Romania. Email address: olic1770@scs.ubbcluj.ro

Department of Computer Science, Faculty of Mathematics and Computer Science, Babeș-Bolyai University, 1 Kogălniceanu, Cluj-Napoca, 400084, Romania. Email address: olic1770@scs.ubbcluj.ro

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Published

2019-06-28

How to Cite

ONAC, L. (2019). TRIST: TREE RECOGNITION INTELLIGENT SYSTEM. Studia Universitatis Babeș-Bolyai Informatica, 64(1), 5–14. https://doi.org/10.24193/subbi.2019.1.01

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Section

Articles