Crop Disease Identification Using Deep Learni...

Crop Disease Identification Using Deep Learning Techniques for Kharif and Rabi Crops

Author Name : Saish Adlak, Deepika Gupta, Rishika Bagga, Noopur Katre, Gayatri Satpute, Dr. Manoj Bramhe, Mohit Agrawal

ABSTRACT

Diagnosis of plant diseases is the basis of preventing plant diseases in a complex environment and therefore it is important that plant diseases are detected as soon as possible. Soon the development of clever farming, the identification of plant diseases they are digitally driven and driven by detail, allowing for advanced decision making support, good analysis, and planning .The proposed system assists in the identification of diseases in plants. The database is available and sorted by various plant species they are identified and renamed for relevant data and testing a database is available containing various images of existing plants used to check the accuracy of the project. Neural Flexibility Networks (CNNs) are responsible for image recognition and offer the ability to provide a quick diagnosis. The database is then retrained then the result is predicted with absolute accuracy. To determine the life of a plant by image, a very difficult task as its evolution is constantly changing all season. Their appearance also changes slightly over time day, such as the number and angle of impact of solar radiation their spectral response. But with our code and training model, we have in achieved an accuracy of 76.2%.

Keywords: - Convolutional Neural Network, classification, accuracy, training model