A fungus that can wipe out up to 50% of a sugar beet crop may soon meet its match in a new generation of smart disease ...
With the continuous expansion of highway networks in recent years, the monitoring and repair of road diseases have become one of the important tasks in traffic management. Traditional manual ...
Abstract: Utilizing state-of-the-art deep learning techniques for intelligent farming is the aim of the YOLOv8 Algorithm. The rapid advancement of AI technologies has made precision farming essential ...
Abstract: Early detection of plant leaf diseases is essential for agricultural productivity and food security. Traditional methods are manual, time consuming, and knowledge dependent. In this paper, ...
We present a deep-learning approach for detecting diseases across multiple crop types using the PlantDoc dataset. Our method combines a classification network and an object detection network to ...
Abstract: Plant diseases seriously affect worldwide crop output, threatening food security and agricultural sustainability. This study solves these issues by introducing a hybrid machine learning ...
Abstract: The Solanum Lycopersicum is among the most extensively cultivated crops and high commercial value in worldwide area. The hybrid Convolutional Neural Networks algorithm in the MATLAB ...
Abstract: There has been increasing concern about the phenomenon of leaf plant diseases over the last few years. Causes for the prevalence of the leaf plant diseases include climate changes and virus ...