Abstract:
Indians make up a substantial share of the world's agricultural population. However, farmers now face a wide range of challenges due to climate change. One of these chall...Show MoreMetadata
Abstract:
Indians make up a substantial share of the world's agricultural population. However, farmers now face a wide range of challenges due to climate change. One of these challenges is a drop in agricultural output, which is mostly brought on by the appearance of plant diseases. In many Asian and African countries, banana plantations dominate the agricultural sector. Researchers were able to recognize and categorize illnesses that affect banana fruit leaves by extracting features using CNN and SVM. They used MATLAB code to improve and prepare the dataset before splitting it 80:20 into training and evaluation sets for this investigation. An incredible 90% average accuracy was achieved via the effective use of CNN and SVM models. This research shows that the suggested model offers an automated and accurate diagnosis of illnesses affecting banana leaves, offering a workable way for precisely identifying crop leaf diseases.
Date of Conference: 01-02 November 2023
Date Added to IEEE Xplore: 03 January 2024
ISBN Information: