Machine Learning Based Weed Crop Classification Using Raspberry PI

Weed-crop classification using machine learning is an emerging area of research in precision agriculture that aims to automate the process of identifying and distinguishing weeds from crops in agricultural fields. Weeds compete with crops for essential resources such as sunlight, water, and nutrients, ultimately reducing crop yield and quality. Traditional weed control methods, including manual weeding and blanket application of herbicides, are often labor-intensive, time-consuming, and environmentally harmful. To address these challenges, machine learning techniques, particularly supervised learning algorithms, have been increasingly applied to develop intelligent systems capable of performing accurate and efficient weed detection and classification.