Mohd Zulhilmi Ab Jamil
Thesis
The productivity of agriculture in Malaysia has improved as the technology advances. However, several concerns need to be considered to maintain the productivity. The growth of plant weeds in the fields is one of the concerns that need to be taken care of as it resulted to the decrease of the crop yield. This paper presents an integrated method for classifying plant weeds through the shape of their leaves by applying neuro-fuzzy techniques. The developed e-prototype is able to classify the weeds with 83.78% accuracy. Hopefully the findings in this study may assist the farmers and researchers in increasing their crop yield.
Fuzzy Logic, Neural Network, Neuro-Fuzzy, Plant Weeds.
Published on 21/09/2016
Submitted on 30/12/2016 01:23:36 pm
Research Interest Group Intelligent Systems, Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA, 40450 Shah Alam, Selangor.
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