This review article provides a comprehensive examination of the state-of-the-art in maize
disease detection leveraging Convolutional Neural Networks (CNNs). Beginning with the …

This study uses a Convolutional Neural Network (CNN) model in conjunction with a
Federated Learning (FL) framework to thoroughly investigate the identification of parsley leaf …

The preservation of wildlife holds significant worldwide significance, particularly in light of
the escalating risks posed to biodiversity and ecosystems. In the present situation, the …

Maize, as one of the most important crops in the world, faces severe challenges from various
diseases and pests. The timely and accurate identification of maize leaf diseases and pests …

A novel method for classifying disease severity in jute leaves is developed using federated
learning and a convolutional neural network (CNN). For this research, four clients with …

The Precise and prompt identification of plant pathogens is essential to keep agricultural
losses as low as possible. In recent time, deep convolution neural networks have seen an …

In this research paper, agricultural diseases can be detected using innovative technologies.
To discuss classification approaches to strawberry leaf disease using a Federated Learning …

This research employs federated learning using Convolutional Neural Networks (CNN)
across multi-institutional datasets to classify the severity of lung disease. The project …

The timely and precise identification of plant diseases is still crucial in precision agriculture
to guarantee maximum crop health and yields. Using a novel combination of Federated …

One crucial crop that stands out in the complex web of agricultural diagnostics is jute, often
called the “Golden Fibre.” However, jute leaf diseases, which may appear in varying …