❄ Major crops today are plagued by a variety of diseases. Diseases in crops can occur in various parts of the plant, such as the roots, stem, but leaves are the most typical site for disease detection.
❄ It is difficult to detect and diagnose diseases because leaves have a variety of sizes, shapes, and colors.
❄ Current disease diagnosis based on human scouting is time-consuming & expensive, however, the advancements of machine learning and computer data processing helped in automatically identify diseases in crops like rice, corn, wheat, cotton & tomato.
❄ The goal of this project is to leverage computer-vision-based techniques and build a model that can:
---- ❄ Accurately classify a given image into a diseased category or a healthy leaf.
---- ❄ Accurately distinguish between many diseases, sometimes more than one on a single leaf.
---- ❄ Deal with rare classes and novel symptoms.
---- ❄ Address depth perception — angle, light, shade & age of the leaf.