Conference paper
Application of cellular neural networks and NaiveBayes classifier in agriculture
9th Conference of the Asian Federation for Information Technology in Agriculture (AFITA) 2014 (Perth, Western Australia, 29/09/2014–02/10/2014)
2014
Abstract
This article describes the use of Cellular Neural Networks (a class of Ordinary Differential Equation (ODE)) , Fourier Descriptors (FD) and NaiveBayes Classifier (NBC) for automatic identification of images of plant leaves. The novelty of this article is seen in the use of CNN for image segmentation and a combination FDs with NBC. The main advantage of the segmentation method is the computation speed compared with other edge operators such as canny, sobel, Laplacian of Gaussian (LoG). The results herein show the potential of the methods in this paper for examining different agricultural images and distinguishing between different crops and weeds in the agricultural system.
Details
- Title
- Application of cellular neural networks and NaiveBayes classifier in agriculture
- Authors/Creators
- O. Babatunde (Author/Creator)L. Armstrong (Author/Creator)J. Leng (Author/Creator)D. Diepeveen (Author/Creator)
- Conference
- 9th Conference of the Asian Federation for Information Technology in Agriculture (AFITA) 2014 (Perth, Western Australia, 29/09/2014–02/10/2014)
- Identifiers
- 991005540370307891
- Murdoch Affiliation
- School of Veterinary and Life Sciences
- Language
- English
- Resource Type
- Conference paper
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