Deep Learning-Based Recognition of Plant Leaf Diseases

Early and accurate disease detection is crucial for effective crop management. This paper proposes a deep learning-based system for automatic plant disease detection using image processing techniques. Our approach leverages Convolutional Neural Networks (CNNs) to analyze images of leaves. The CNN is trained to identify various diseases based on visual symptoms like black and brown spots, mimicking the methods employed by human professionals. This system offers real-time crop monitoring and eliminates the need for farmers to switch between multiple disease control strategies without proper diagnosis. By analyzing image features, the system automatically categorizes the disease present in a captured image. Our research demonstrates that this approach achieves high accuracy in disease detection, potentially leading to improved crop health and yield.