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Authors: Andre Abade 1 ; Ana S. de Almeida 2 and Flavio Vidal 3

Affiliations: 1 Federal Institute of Education, Science and Technology of Mato Grosso, Brazil ; 2 Department of Mechanical Engineering, University of Brasilia, Distrito Federal, Brazil ; 3 Department of Computer Science, University of Brasilia, Distrito Federal, Brazil

ISBN: 978-989-758-354-4

Keyword(s): Convolutional Neural Networks, Multichannel Convolutional Neural Networks, Plant Disease, Crop Disease Recognition, Computer Vision.

Abstract: Plant diseases are considered one of the main factors influencing food production and to minimize losses in production, it is essential that crop diseases have a fast detection and recognition. Nowadays, recent studies use deep learning techniques to diagnose plant diseases in an attempt to solve the main problem: a fast, low-cost and efficient methodology to diagnose plant diseases. In this work, we propose the use of classical convolutional neural network (CNN) models trained from scratch and a Multichannel CNN (M-CNN) approach to train and evaluate the PlantVillage dataset, containing several plant diseases and more than 54,000 images (divided into 38 diseases classes with 14 plant species). In both proposed approaches, our results achieved better accuracies than the state-of-the-art, with faster convergence and without the use of transfer learning techniques. Our multichannel approach also demonstrates that the three versions of the dataset (colored, grayscaled and segmented) can contribute to improve accuracy, adding relevant information to the proposed artificial neural network. (More)

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Paper citation in several formats:
Abade, A.; S. de Almeida, A. and Vidal, F. B. (2019). Plant Diseases Recognition from Digital Images using Multichannel Convolutional Neural Networks.In Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP, ISBN 978-989-758-354-4, pages 450-458. DOI: 10.5220/0007383904500458

@conference{visapp19,
author={Andre da Silva Abade. and Ana Paula G. S. de Almeida. and Vidal, F. B.},
title={Plant Diseases Recognition from Digital Images using Multichannel Convolutional Neural Networks},
booktitle={Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP,},
year={2019},
pages={450-458},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007383904500458},
isbn={978-989-758-354-4},
}

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP,
TI - Plant Diseases Recognition from Digital Images using Multichannel Convolutional Neural Networks
SN - 978-989-758-354-4
AU - Abade, A.
AU - S. de Almeida, A.
AU - Vidal, F. B.
PY - 2019
SP - 450
EP - 458
DO - 10.5220/0007383904500458

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