The increased demand for food is accelerating plant diseases globally. Hence, a manual
process of detection of plant diseases is almost impossible. Artificial intelligence (AI) can …

Deep learning has emerged as an effective tool for fixing a diffusion of image processing
responsibilities such as object detection, category, segmentation, and reconstruction. This …

Abstract The UN Sustainable Development Goals (SDGs) enhance health, ecology, vitality,
and the global economy. This chapter carefully reviews scholarly literature to identify …

This chapter highlights the importance of automated plant disease analysis for agricultural
enhancement. It addresses two critical challenges: disease identification and severity …

This paper delves into the realm of artificial intelligence, where an array of deep learning
techniques has proven effective in automating crop leaf disease identification and …

Existing approaches often fail to capture the complex spatial-temporal interactions among
crop conditions, environmental factors, and disease progression, leading to suboptimal …

INTRODUCTION: Plant diseases pose a significant threat to agriculture, causing substantial
crop and financial losses. Modern technologies enable precise monitoring of plant health …

“FarmEasy” will be a single platform for all activities related to farming and crop diagnostics.
The platform's ability to detect and recognize pests is its most crucial component. In the …

The identification and categorization of Bottle Gourd leaf illnesses across various severity
levels are presented in this research as a unique application of the foundation of the study is …

The urgent necessity to bolster agricultural productivity while ensuring quality control has
amplified the demand for advanced diagnostic methods for fruit disease detection. Thermal …