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Agriculture is the greatest labor agency in Bangladesh. As our country is an agricultural
country; Most of the people of Bangladesh depends on agricultural products for their
livelihood. Lack of opportunities and facilities, natural disasters, diseases of crops are
main obstacles in growth of agricultural sector in our country. Diseases in plants are a
significant yield and quality constraint for growers of broad acre crops. As important
agricultural crops are under threat due to various plant diseases and pests and the quality
of the crop can be affected by various diseases. So, it is very necessary to detect the
disease at the proper period to the cultivator. When crop disease could be easily track
out, then it can be effective for monitoring and restrain disease for agriculture and food
safety. We have worked with cucumber disease detection in our project because
cucumber is much needed grain in our country. If the cucumber is affected, it will cause
huge damage to the economy of the country. Since cucumber has many qualities, if it
is transited, it will have a huge detrimental effect on nutrition. A system called computer
vision and machine learning is used to detect crop disease promptly and accurately
which we used to detect cucumber diseases. Diagnosis of plant disease through this
technology is very profitable and easy. This is because it reduces huge workload of crop
monitoring and it can detect the symptoms of all diseases at very early stage. This
system includes pattern recognition and creating database and classification,
approximation, optimization, and data clustering. We are going to implement this goal
by thinking of the people and helping the farmers to cultivate properly. |
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