Comparative analysis to improve accuracy of cotton leaves disease detection system using MobileNet and VGG.

The goal of this study is to provide an accurate and innovative approach for cotton leaf disease detection by using mobilenet and VGG algorithms to detect disease and comparing their accuracy. Materials and Methods: The sample size for Mobile net (N=10) and for VGG (N=10) was iterated 20 times to predict cotton leaf disease. Results: Mobile net has significantly better accuracy (96.97%) compared to VGG accuracy (89.87%). The statistical significance difference 0.01 (p<0.05 independent sample test) value states that the results in the study are significant. Conclusion: Theresults depicted that mobile net provides good results in detecting cotton leaf disease over VGG. [ABSTRACT FROM AUTHOR]