Utilization of Cutting-Edge Sequential CNN Models for Precise Classification of Coffee Leaf

A major part of the world economy and agriculture is played by the coffee business. Optimising output and guaranteeing sustainable production need constant monitoring of the health and categorization of coffee plants. Many diseases and insects are quite sensitive to coffee plants. Overuse of pesticides can eventually create disease resistance, which would severely limit the ability of coffee plants to fend off infections. This effort aims on creating a sophisticated deep learning-based Sequential Convolutional Neural Network (CNN) model for coffee leaf classification and visualisation. A novel deep learning-based Sequential CNN model is presented in this work to visualise and classify coffee leaves. India's coffee crop yield may increase if coffee plant growers use the previously described method to identify diseases more quickly. The approach that was proposed was developed to support farmers and the agricultural sector. The developed model therefore exhibits encouraging accuracy and interpretability results, which will fuel the expansion of precision agriculture in the coffee industry.