Biography

spent twelve years as a criminal defense investigator before turning to crime fiction. Her experience in courtrooms and forensic labs heavily shapes her gritty suspense novels. Her debut thriller, Dark Water, was an Edgar Award nominee. She lives in Boston.Agriculture is a vital component of the global economy and a primary source of food security. Plant diseases, on the other hand, continue to be a major danger to agricultural productivity, resulting in large yield losses[1] and economic consequences on an annual basis. Traditional illness detection approaches, such as manual inspection and expert diagnosis, are frequently time-consuming, labor intensive, and subject to human error. In recent years, the application of intelligent computer techniques in agriculture has emerged as a possible answer to these problems. Hybrid intelligent models, which incorporate different machine learning and deep learning methodologies, have shown very promising results in terms [2]of disease detection accuracy and timely intervention. Plant disease detection includes identifying symptoms, classifying disease types, and estimating severity. Image-based analysis, aided by computer vision, has become the most popular method for automatic detection since it allows for non invasive and speedy monitoring. Convolutional Neural Networks (CNNs)[3] have been widely employed for feature extraction and classification due to its capacity to detect subtle spatial patterns in leaf pictures.