Plant Disease Detection by Using Adaptive Neuro-Fuzzy Inference System

Rabia Bayraktar,Bülent Haznedar,Kadir Sercan Bayram,Muhammet Fatih Hasoğlu

Keywords: ANFIS, Plant Diseases, Recognition, Detection

Abstract: This study aims the detection and recognition of plant diseases by using the most modern methods including Support Vector Machine (SVM), Convolution Neural Network (CNN), Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Interface System (ANFIS). In the studies, 2340 training and 585 test data were used with 3 different tomato plant leaves as Healthy, Early blight, and Yellow leaf curl virus. These methods are used in a wide spectrum of research areas. While creating the dataset, a total of 11 features were extracted from the existing image data. 91% accuracy has been achieved with the proposed ANFIS which is the best compared to the other methods with 11 features.

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