Recent Advances in Deep Learning CNN Models for Plant Disease Detection

Abstract

Machine learning and deep learning techniques are being used frequently in recent days for plant disease detection. The deep CNN models have been used in different fields and have gained immense result. With the growing population in the world, the importance of plant protection that produces food is also tremendously increasing. Various recent works have applied deep CNN models in the agricultural field and contributed a lot to specially w.r.t. various disease detection. It not only gives high prediction accuracies but also improves the other parameters, i.e., sensitivity, specificity, and F1 score of the model, which signifies better model for plant disease detection. Here, a survey of papers has been presented showing the use of different pre-trained CNN models in the field of plant disease detection. The summarized findings clearly indicate that CNN models are enriched with techniques that give promising performance with better precision and accuracy.