Abstract
The goal of the proposed study is to use ResNet rather than a novel recurrent neural network to identify plant diseases with greater classification accuracy. Materials and Methods: The detection of plant disease is performed using ResNet and Recurrent Neural Network algorithms. The sample size for each sample is considered as 10 which is performed with a G power calculator. Results: The ResNet algorithm exhibited better results with classification accuracy of 95% compared to that of Novel Recurrent Neural Network with accuracy of 85%. The insignificant accuracy value of p=0.139 (p>0.05) is attained through SPSS Statistical Analysis.
Conclusion: The classification of plant disease using ResNet is better than the Novel Recurrent Neural Network.