Plant Leaf Disease Detection Using Machine Learning.

Computer Engineering

The detection of plant leaf is very important factor to prevent serious outbreak. Automatic detection of plant disease is essential research topic. Most plant diseases are caused by fungi, bacteria, and viruses. Fungi are identified primarily from their morphology, with emphasis placed on their reproductive structures. Bacteria are considered more primitive than fungi and generally have simpler life cycles. With few exceptions, bacteria exist as single cells and increase in numbers by dividing into two cells during a process called binary fission. Viruses are extremely tiny particles consisting of protein and genetic material with no associated protein. The term disease is usually used only for the destruction of live plants. The proposed processing scheme uses machine learning and dynamic plants image model to predict disease related to the leaf. Using machine learning makes platform generic and useful. Adding and updating new diseases and datasets is easy if machine learning is use. Using cloud computing for storing retrieving and serving data from machine learning model is efficient choice and both technologies can be used to create system.

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