Abstrakt

Detection of Banana Leaf Disease and its Analysis Using Different Techniques

Arjun Jadhaw, Rajat Bhandari

Banana cultivation is the one of the major agriculture elements in India. As same time common problem of cultivation is that crop has been influenced by way of numerous illnesses. Early disease diagnosis is very important for banana production and crop management. Banana diseases are responsible for loses that directly impact on global fruit production and management system, resulting in economic losses of country. Proposed method combined with modified convolutional neural network and Region-Based segmentation with optimal threshold technique enabled banana disease detection and classification is proposed to overcome these issues and guide the farmers through enabling fertilizer that have to be utilized for avoiding the disease in the initial stage. The purpose of this paper is to introduce various deep learning techniques including convolutional neural network, support vector machine, AlexNet, ResNet-50, artificial neural network and VGG-16. This study has the capacity to motivate the researchers to utilize the article to better understanding of related disease prediction algorithms.