The Neural Farmer

This book explores the application of deep learning, specifically Convolutional Neural Networks (CNNs), for the automated detection and classification of potato leaf diseases such as early blight and late blight. It provides a comprehensive overview of traditional diagnostic methods, the fundamentals of CNNs, dataset preparation, model architecture, training strategies, and evaluation metrics. With an emphasis on practical applications, the book also addresses limitations like dataset bias, image quality, and model interpretability. Designed for researchers, students, and agricultural practitioners, this work contributes to the growing field of AI-driven precision agriculture, promoting sustainable and intelligent farming solutions.

Autorentext

Prakhar is a passionate researcher in the field of artificial intelligence and its applications in agriculture. With a keen interest in deep learning and sustainable farming technologies, he aims to bridge the gap between modern innovation and practical rural solutions.