Stratification of Parsley Leaf Crown Disease Using a Blended CNN Model based on Deep Learning

The study has placed a significant emphasis on the application of tasks involving computer vision to the characterization and classification of phytopathogens. Even though herbs are additionally Nutritious plants and may get sick, identifying herb ailments has been hampered as a result of the significant amount of research that has been focused on plant ailments. An algorithm for the being identified, naming, and categorization of parsley disease has been created. The goal of this algorithm is to recognize and classify the parsley leaf crown (PLC) illness according to its degree of severity. The suggested technique uses a deep learning-based neural network convolutional(CNN)-based computer modeling (DL) model to identify 200 photos of parsley leaves PLS unhealthy images. It achieves an accuracy rate of 99.5% in inter of the PLC illness, and it does this using a deep learning approach. Regarding PLS disease multi-classification, the suggested model is superior to other pre-trained models, as is shown by comparisons between those models and the proposed technique.