Precision agriculture relies on the early detection and isolation of crop diseases, and this
research details how the You Only Look Once, Version 8 (YOLOv8) algorithm was used for …

Plant diseases pose a significant threat to global agriculture, resulting in substantial crop
losses each year. To address the pressing need for rapid and accurate disease …

Agriculture faces a significant challenge with leaf disease, which can lead to substantial
decreases in crop productivity. Deep learning techniques, particularly the YOLO (You Only …

The presence issue of inaccurate plant disease detection persists under real field conditions
and most deep learning (DL) techniques still struggle to achieve real-time performance …

Corn crop disease detection is crucial in ensuring crop health and optimizing agricultural
productivity. This study explores the implementation of the YOLOv8 algorithm for efficient …

Preventing and managing plant leaf diseases requires a dependable and precise detection
method. Detecting leaf diseases in plants is a time-consuming process that has a negative …

The current paper explores the close interaction between technological advancements and
the field of agriculture through a project focused on plant disease detection using Deep …

Agriculture is a mainstay of the Moroccan economy and the breadwinner for millions of
farmers, offering them a broad array of crop varieties. However, a lack of resources and …

Detecting plant leaf diseases accurately and promptly is essential for reducing economic
consequences and maximizing crop yield. However, farmers' dependence on conventional …

Recognizing plant diseases is crucial for agricultural sustainability and high-quality produce.
The conventional manual method of monitoring plant diseases is labor-intensive, requires …