Volume - 13 | Issue-1
Volume - 13 | Issue-1
Volume - 13 | Issue-1
Volume - 13 | Issue-1
Volume - 13 | Issue-1
Aim: To estimate accuracy in Image plant disease detection using Convolutional Neural Network over Fully Connected Neural Network. Materials and Methods: Convolutional Neural Network and Fully Connected Neural Network are implemented in this research work. Sample size is calculated using G power software and determined as 10 per group with pretest power 80%. Results and Discussion: Convolutional Neural Network provides a higher of 89.00 compared to Fully Connected Neural Network with 81.52 in predicting plant disease in plant diseases detection. There are statistically significant differences between study groups with p = 0.035 (p<0.05). Independent T-test value states that the results in the study are insignificant. Conclusion: Convolutional Neural Network gives better accuracy then Fully Connected Neural Network.