Cpd-ccnn: Classification Of Pepper Disease Using A Concatenation Of Convolutional Neural Network Models

This research presents the development of a concatenated classification model for pepper leaf and fruit disease classification. The paper is organized based on sections such as related work, methodology, results and discussion, and conclusion. The research focused on pepper leaves and fruit disease classification using a concatenation of convolutional neural network (CNN) models to identify healthy pepper leaves, common rust in pepper leaves, gray-leaf spot in pepper leaves, fruit disease, and blight disease in pepper leaves. The authors compared CNN architectures such as VGGNet, ResNet, and InceptionNet and achieved an accuracy of 97.84%.