CROP DISEASE DETECTION MOBILE APPLICATION
DOI:
https://doi.org/10.17605/OSF.IO/QVESXKeywords:
Convolutional neural network, Crop Diseases, Deep neural networkAbstract
India being one of the major agricultural producing countries relies majorly on food production. The primary source of income in India is also through agriculture. Agriculture is also a primary source of employment, food and income for many citizens of India. There are many factors that are responsible for good agricultural production. Some of the factors include usage of fertilizers, amount of rainfall, proper distribution of rainfall, fertility of soil, quality of soil etc. The major issue which is faced by people is the crop diseases. Crop diseases also act as a major threat for small scale farmers because it may lead to destruction in their whole food supply. Sometimes farmers are not fully aware of the diseases which can lead to false determination of disease and improper solution of the problem. Farmers often tend to use wrong fertilizers or wrong amounts of fertilizers which may lead to crop failure. Farmers usually identify the disease through their naked eyes which eventually leads them to make wrong predictions about the disease. As a solution to this problem, this mobile application focuses on identifying the right disease and also to provide the solutions for the same. This mobile application can run in Android as well as iOS which make it more usable. It uses machine learning and deep learning for disease detection in the crops. Deep neural network and Convolutional neural network, parts of deep learning have been used to detect diseases.
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